Courses

  • A101 | Elective

    Adaptive Systems

    Kenji Doya

    Explore common mathematical frameworks for adaptation at different scales and link them with biological reality.  The course is in a "flipped learning" style; each week, students read a book chapter and experiment with sample codes before the class.
    In the first class of the week, they present what they have learned and raise questions.
    In the second class of the week, they 1) present a paper in the reference list, 2) solve exercise problem(s), 3) make a new exercise problem and solve it, or 4) propose revisions in the chapter.
    Toward the end of the course, students work on individual or group projects by picking any of the methods introduced in the course and apply that to a problem of their interest.
     

    Prior knowledge

    Assumes good knowledge of Python, statistics, and an ability to look at biological problems in a mathematical way.   OIST courses to complete beforehand:  B31 Statistical Tests 

    3 Term

    2 Credits

  • A203 | Elective

    Advanced Optics

    Síle Nic Chormaic

    Review of geometrical optics; wave properties of light and the wave equation; Helmholtz equation;  wave optics, including Fresnel and Fraunhofer diffraction, transfer functions, coherence, auto and cross-correlation;  Gaussian and non-Gaussian beam profiles; quantum optics and photon statistics; spin squeezing; applications of optics including fiber optics, laser resonators, laser amplifiers, non-linear optics, and optical trapping; quantum properties of light; interaction of photons and atoms.

    2 Term

    2 Credits

  • A210 | Elective

    Advanced Quantum Mechanics

    Thomas Busch

    Advanced course in Quantum Mechanics, based on recent theoretical and experimental advances. Evolution in Hilbert space and quantum bits; conditional quantum dynamics; quantum simulations; quantum Fourier transform and quantum search algorithms; ion-trap and NMR experiments; quantum noise and master equations; Hilbert space distances; Von Neumann entropy; Holevo bound; entanglement as a physical resource; quantum cryptography; lab: quantum eraser, interaction free measurement.

    Prior knowledge

    Solid undergraduate Quantum Mechanics preparation.  Students may wish to take this with A273 Ultracold Quantum Gasses and A218 Condensed Matter Physics.

    2 Term

    2 Credits

  • A211 | Elective

    Advances in Atomic Physics for Quantum Technologies

    Síle Nic Chormaic

    Advanced level course in atomic physics.   Progress in laser control of atoms has led to the creation of Bose-Einstein condensates, ultrafast time and frequency standards and the ability to develop quantum technologies. In this course we will cover the essentials of atomic physics including resonance phenomena, atoms in electric and magnetic fields, and light-matter interactions.   This leads to topics relevant in current research such as laser cooling and trapping.

    2 Term

    2 Credits

  • B10 | Elective

    Analytical Mechanics

    Mahesh Bandi

    Explore the concepts and techniques of classical analytical mechanics so essential to a deep understanding of physics, particularly in the areas of fluid dynamics and quantum mechanics. Develop from the basic principles of symmetry and least action to the Galilean, Lagrangian, and Newtonian equations of motion and laws of conservation.  Use the Lagrange formalism to describe particle motion in multiple modes, before exploring the equations of Euler and Hamilton, and canonical transformations.  Use the calculus of variation to develop Maupertuis's principle and the Hamilton-Jacobi equations, and build a starting point for the consideration of waves in other courses.  Ongoing homework exercises and small exams provide continuing assessment.

    Prior knowledge

    College level introductory physics or permission of instructor, mathematics for physics.  

    1 Term

    2 Credits

  • A208 | Elective

    Bioorganic Chemistry

    Fujie Tanaka

    Design and synthesize small organic functional molecules for understanding and controlling biological systems. Build a strong foundation of modern synthetic organic chemistry strategies, including stereoselective, enantioselective, and asymmetric methods.  Through lectures and literature studies, explore a range of mechanisms of catalytic reactions controlling reaction pathways and molecular interactions essential in organic reactions and in the design and synthesis of catalysts, functional small organic molecules, and protein conjugates.

    Prior knowledge

    Requires undergraduate organic chemistry or biochemistry.

    2 Term

    2 Credits

  • B21 | Elective

    Biophysics of Cellular Membranes

    Akihiro Kusumi

    Explore concepts of biophysics including thermal conformational fluctuation and thermal diffusion, and consider how cells might take advantage of these physical processes to enable their functions. Discover how the cell membrane system functions in light of these physical processes to fulfil its critical contribution to cell signal transduction and metabolism.  With extensive use of student presentations about topics of cellular signaling in the context of cellular cancer biology, immunology, and neurobiology, discuss the dynamic structures of the plasma membrane, including domain structures, tubulovesicular network, endocytosis and exocytosis, and cytoskeletal interactions. Learn methods of single-molecule imaging-tracking and manipulation for directly “seeing” the thermal, stochastic processes exhibited by receptors and downstream signaling molecules during signaling in live cells.

    Prior knowledge

    Biology, chemistry, and/or physics at undergraduate levels

    3 Term

    2 Credits

  • B11 | Elective

    Classical Electrodynamics

    Tsumoru Shintake

    Learn the theory and application of classical electrodynamics and special relativity, covering the essential equations and their applications, and build a firm grounding for later studies of quantum physics.  Through lectures and exercises, an understanding of static electromagnetic fields is extended through Maxwell’s equations to a discussion of dynamic vector fields and electromagnetic waves. Numerous physical and technical applications of these equations are used to illustrate the concepts, including dielectrics and conductors, wave guides, and microwave engineering.  Special relativity is introduced with discussion of relativistic and non-relativistic motion and radiation, using linear accelerators and synchrotron radiation as illustrative applications. Demonstrate understanding and application of these concepts in mid-term and final exams. 

    Prior knowledge

    Undergraduate level knowledge of mechanics, and calculus and vector mathematics.

    2 Term

    2 Credits

  • A313 | Elective

    Cognitive Neurorobotics

    Jun Tani

    Explore the principles of embodied cognition by a synthetic neurorobotics modeling approach in combination with hands-on neurorobotics experiments and related term projects. Combine related interdisciplinary findings in artificial intelligence and robotics, phenomenology, cognitive neuroscience, psychology, and deep and dynamic neural network models. Perform neurorobotics simulations and control experiments with extensive coding in C++ or Python.  Critically analyze and report on recent papers in neurorobotics and artificial intelligence.

    Prior knowledge

    Basic mathematical knowledge for the calculus of vectors and matrices and the concept of differential equations are assumed.   B46 Introduction to Machine Learning (or similar) and programming experience in Python, C or C++ are required.

    1 Term

    2 Credits

  • A106 | Elective

    Computational Mechanics

    Marco Edoardo Rosti

    Numerical solutions to partial differential equations have wide application in many areas of physics, mechanics, engineering, and applied mathematics.  Learn different techniques for solving elliptic, parabolic and hyperbolic  equations, such as finite differences and finite volumes. Discuss possibilities and limitations of numerical techniques. Evaluate and comment on the stability and convergence of these numerical methods. Explore systems of partial differential equations and the Navier-Stokes equations. Use Python or MATLAB coding in weekly exercise sessions to numerically solve diffusion, convection and transport problems in multiple dimensions.  

    Prior knowledge

    Requires good background in partial differential equations. A basic knowledge of Python, MATLAB or any other programming language is preferred but not essential.

    3 Term

    2 Credits

  • A310 | Elective

    Computational Neuroscience

    Erik De Schutter

    Explore topics in computational neuroscience, from single neuron properties to networks of integrate-and-fire neurons. Review the biophysical properties of neurons and extend these findings to cable theory and passive dendrite simulations. Study excitability based on the Hodgkin-Huxley model of the action potential and the contributions of various other ion channels. Review phase space analysis, reaction-diffusion modeling and simulating calcium dynamics. Model single neurons, neuronal populations, and networks using NEURON software. Discuss seminal papers associated with each topic, and produce reports on modeling exercises.

    Prior knowledge

    Requires introductory neuroscience course or equivalent with background knowledge in computational methods, programming, mathematics.

    2 Term

    2 Credits

  • A218 | Elective

    Condensed Matter Physics

    Yejun Feng

    Condensed matter physics has evolved from solid state physics into a subject which focuses on collective behavior, symmetry, and topological states.  This course provides an introduction to the field, arranged along three major concepts of lattice, electrons, and spins. We survey both central theoretical concepts and their experimental demonstrations, such as Landau levels and quantum Hall effects, superconductivity, and magnetic excitations. Several of these topics are developed from fundamental concepts to an advanced perspective.

    Prior knowledge

    Undergraduate level quantum mechanics and statistics.

    2 Term

    2 Credits

  • B34 | Elective

    Coral Reef Ecology and Biology

    Timothy Ravasi

    Discover the largest and most complex biological structures on earth in this introduction to tropical coral reefs and the organisms and processes responsible for their formation. From an overview of reefs and their tropical marine environment, expand into the evolution, systematics, physiology, ecology and symbiosis of reef building corals. Learn about structure and ecological dynamics of coral reef fish communities, and the major characteristics of other key animals and plants on reefs. Recognize key processes on shallow and deep reefs, and variability among reefs, including those of the Okinawan area.  Examine cutting-edge questions in coral reef biology and conservation. Critically analyze natural and human disturbances to reefs with an emphasis on current models of management and conservation.  Design a marine refuge area based on ecological and conservation principles. Develop practical skills in sample and survey methods via snorkeling activities. 

    Prior knowledge

    Undergraduate knowledge of general biology and zoology. Able to swim and snorkel for the field trip component of the course.

    3 Term

    2 Credits

  • A303 | Elective

    Developmental Biology

    Ichiro Masai

    Learn fundamental principles and key concepts in the developmental processes of animal organisms.  One model system is Drosophila, looking at embryonic development of body plan patterning and subsequent organogenesis. Another model is vertebrate neural development in zebrafish, looking at vertebrate body plan, cell fate decisions, neuronal specification, axon guidance and targeting, and synaptogenesis.  Extend these bases by practical exercises using genetic tools for live imaging of fluorescence-labeled cells using Drosophila and zebrafish embryos. Debate specific topics in developmental biology and apply these findings by writing a mock grant application.  Occasional guest lectures on special topics.

    Prior knowledge

    Cell biology at undergraduate level.

    2 Term

    2 Credits

  • B49 | Elective

    Dynamical Systems

    Mahesh Bandi

    An introduction to chaos theory and related topics in nonlinear dynamics, including the detection and quantification of chaos in experimental data, fractals, and complex systems. Most of the important elementary concepts in nonlinear dynamics are discussed, with emphasis on the physical concepts and useful results rather than mathematical proofs and derivations: there are several other resources for the latter. Courses in Chaos & Nonlinear Dynamics tend to be either purely qualitative or highly mathematical; this course attempts to fill the middle ground by giving the essential equations, but in their simplest possible form.

    Prior knowledge

    Graduate Classical/Analytical Mechanics

    2 Term

    2 Credits

  • A409 | Elective

    Electron Microscopy

    Matthias Wolf

    An introduction to transmission electron microscopy techniques and applications in biology.  Learn important concepts of the physics of image formation and analysis, which require a basic level of mathematics. Learn about sample handling, contrast enhancement, alignment, and image processing.  Read and analyze relevant scientific papers and discuss jointly during student presentations. Practical demonstrations and hands-on exercises provide an opportunity to comprehend the concepts by experimenting with commonly-used image processing software. An emphasis will be given to highlighting common properties between diffraction and image data and how to take advantage of tools from both techniques during the final image processing projects.

    Prior knowledge

    Undergraduate mathematics.

    3 Term

    2 Credits

  • A308 | Elective

    Epigenetics

    Hidetoshi Saze

    Epigenetic regulation of gene activity is essential for development and response to environmental changes in living organisms. Discover fundamental principles and key concepts of epigenetics, including the specific molecular mechanisms and structural changes. Examine these changes in the context of modifying factors such as transposable elements, RNA interference, and dosage compensation. Discuss recent advances in epigenetic reprogramming, stem cell applications, and the influence of epigenetic changes on disease. Critically review and discuss original research publications about epigenetic phenomena.

    Prior knowledge

    Requires at least advanced undergraduate level Cell Biology and Genetics or similar background knowledge

    3 Term

    2 Credits

  • A304 | Elective

    Evolutionary Developmental Biology

    Noriyuki Satoh

    Learn about the most recent theory and techniques in evolutionary and developmental biology with an emphasis on the underlying molecular genomics. Trace the history of animal body plans, and consider the genetic toolkits responsible for this evolution. Examine recent advances in decoding the genomes of various animals, plants and microbes. Through class presentations, critically analyze research in developmental biology and present findings on topics such as comparative genomics, the evolution of transcription factors and signal transduction molecules and their relation to the evolution and diversification of the various complex body plans present through history.  

    Prior knowledge

    Undergraduate level Cell Biology and Genetics or similar background knowledge required.

    3 Term

    2 Credits

  • B41 | Elective

    Fundamentals of Ecology

    David Armitage

    Investigate the fundamental question of ecology: the processes that determine the distribution and abundance of organisms.  Through reading, discussion, and lecture, explore the principles governing population dynamics over time and space, theories of community assembly and species coexistence, and processes of material cycling through ecosystems. Differentiate and critique major theories of population and community ecology, develop and analyze simple population dynamic models, critically evaluate primary literature and cogently summarize a scientific controversy through writing.  Beyond the core subject matter, identify more general principles of the causal feedbacks, scale dependencies, and contingencies of complex social systems.

    Prior knowledge

    Undergraduate level biology and calculus recommended but not required.

    1 Term

    2 Credits

  • A219 | Elective

    General Relativity

    Yasha Neiman

    We begin by introducing tensors in non-relativistic physics. We then give an overview of Special Relativity, and discuss the special nature of gravity as an “inertial force”. With this motivation, we develop the differential geometry necessary to describe curved spacetime and the geodesic motion of free-falling particles. We then proceed to Einstein’s field equations, which we analyze in the Newtonian limit and in the linearized limit (gravitational waves). Finally, we study two iconic solutions to the field equations: the Schwarzschild black hole and Friedman-Robertson-Walker cosmology. We will use Sean Carroll’s textbook as the main reference, but we will not follow it strictly.

    This is an alternating years course.

    Prior knowledge

    Maxwell’s equations in differential form. Solving Maxwell’s equations to obtain electromagnetic waves. Linear algebra of vectors and matrices.

    1 Term

    2 Credits

  • B35 | Elective

    Genetics and Modern Genetic Technologies

    Tomomi Kiyomitsu

    A hands-on introduction to the key concepts of genetics and advances in modern genetic technologies. Learn about fundamental principles of genetics underpinning biologically inherited traits, from classical population genetics to modern molecular genetics.  Investigate modern genetic technologies for sampling, analysing, and editing genes and experience gene manipulation in the laboratory using CRISPR/Cas9 technology in cultured cells. Discuss the various advantages, drawbacks, and ethics of particular gene-editing technologies.

    Students who complete this course will understand the key concepts of genetics and the advantages of modern genetic technologies. In addition, through the exercise of genome editing using cultured human cells, students can realize the power, simplicity of use, and potential risks of genome editing technologies.

      Prior knowledge

      No prerequisite courses. Suggested to take this course alongside/after B27 Molecular Biology of the Cell

      1 Term

      2 Credits

    1. B38 | Elective

      Human Subjects Research: A Primer

      Gail Tripp

      Explore and discuss the particular requirements of research with human subjects with reference to conceptualization, research design, sampling and data collection methods, ethics, and statistical treatment of data.  Learn how to formulate clear and testable hypotheses; describe different sampling methods, their strengths and limitations; identify any ethical issues or concerns for a given research study;  evaluate the strength of different research designs, together with their appropriateness for addressing different research questions; judge the quality of research methods and measures based on indices of reliability and validity. Prepare information letter(s) and consent form(s) and develop a grant application/research proposal (background, hypotheses, methods, statistical analyses, significance) for a human subjects research study. Present a research report on a topic of interest. The emphasis is on behavioral sciences research, but the content can apply to many fields of study.

      Prior knowledge

      There are no prerequisites for this course. Students will be expected to complete assigned readings ahead of class in order to participate fully. 

      1 Term

      2 Credits

    2. B15 | Elective

      Immunology

      Hiroki Ishikawa

      In this course, students will learn basic principles of immunology including the cellular and molecular mechanism of innate and adaptive immunity. The course also provides the clinical importance of immunology in various diseases such as HIV/AIDS, autoimmunity and allergy. Then, students will learn how the immune response can be manipulated by vaccination to combat infectious diseases and cancer.

      3 Term

      2 Credits

    3. IND | Elective

      Independent Study: Directed Study

      The course Independent Study will foster the development of independent study and research skills such as reading and critiquing the scientific literature, formulating scientific questions, and integrating knowledge into a coherent synthesis. Students will undertake a self-directed program of reading and synthesis of ideas.  This course option must be conducted under the guidance of an OIST faculty member acquainted with such work (the 'Tutor'), who will guide the learning, assess the student's progress, and provide an evaluation at the end of term.

      Students should, under supervision of the Tutor, prepare a plan of the study, carry out the appropriate reading and tasks, and then describe the results of their study in a substantial report or essay.  Student and Tutor should agree on the extent of supervision provided, such as timing and format of face-to-face meetings (20 hours required), progress checks, and so on, and the specific assessment tasks for evaluation.  This should be detailed in the proposal, and the Student and Tutor should commit to this undertaking. 

      Proposed Independent Studies require approval by the Curriculum and Examinations Committee.  Applications should be made at the start of a term, to allow sufficient time for study.  This course may be taken in any one term, and should be completed within the period of that term.  The due date for all work will be at the end of the current term. 

      Students may include as part or all of the content of an Independent Study various online courses from a range of educational sources, including Udemy, edX, Datacamp, and Coursera.  If payment is required for participation in or completion of an online course, contact Curriculum and Programs section before enrolling or applying.  Under the supervision of the responsible OIST faculty, you should not need an actual certificate of completion as they will conduct the assessment.

      This course may be taken multiple times for additional credit, using new material.

      Revised September 1, 2023 (for AY2023)

       

       

      All Term

      1 Credits

    4. A213 | Elective

      Inorganic Electrochemistry

      Julia Khusnutdinova

      Discover the principles of electrochemistry with a particular focus on redox behavior of transition metal complexes including metalloproteins. Review the application of transition metal complexes as catalysts for renewable energy storage and production, including metal-catalyzed water oxidation, proton reduction and CO2 reduction processes. Learn to perform cyclic and pulsed voltammetry, electrolysis, and spectroelectrochemistry in the laboratory. Course evaluation will be done based on weekly lab reports and homework, class presentation and final exam. 

       

       

       

      Prior knowledge

      Undergraduate chemistry

      1 Term

      2 Credits

    5. IWS | Elective

      International Workshop Participation

      Workshops, defined as residential short courses in particular topics in a specific scientific or mathematical discipline, and sometimes referred to as Summer Schools, or Winter Schools, etc., are a recognized means of undergoing intensive training in a specific topic or technique. In such workshops, some of the leading scientists in an area gather to share ideas, to keep each other up-to-date in the latest techniques and developments, and to teach senior students.  Approved workshops for award of credit should comprise an intense two - three week period of lectures and exercise sessions, with at least 40 hours of instruction, and be at a level that is accessible to doctoral students.  

      International workshops (which may be held in OIST, in Japan, or overseas) must be approved by the CEC as meeting criteria including sufficient content, quality of instruction and instructors, duration, and other criteria as may be deemed necessary. Preference for approval is given to workshops that include assessment and provide a transcript or report from the organisers to OIST.

      Students who wish to receive credit for attending such a workshop should first seek approval (before booking travel and registration) from the Graduate School, who will check that the workshop meets approval criteria.  The workshop must be appropriate and relevant to the student’s intended thesis research, and be endorsed by the thesis supervisor and academic mentor.

      Please use the form at THIS LINK to apply.

      All Term

      1 Credits

    6. B48 | Elective

      Introduction to Complexity Science

      Ulf Dieckmann

      In this course we will explore together the many facets of complex systems. Complex systems are ubiquitous and play key roles in physical nature, biological life, and social dynamics. We will address the following questions: What is systems thinking, and how can it help us recognize commonalities across disciplines and domains of application? How can complex systems be understood and modeled, including their structure, dynamics, agency, and function? What are the key tools in a complexity scientist’s toolbox? Addressing these questions, we will use a cross-disciplinary approach suitable for students with backgrounds in physics, chemistry, biology, neuroscience, social sciences, mathematics, and computer science.

      Prior knowledge

      Basics of calculus, linear algebra, and programming.

      2 Term

      2 Credits

    7. B37 | Elective

      Introduction to Embodied Cognitive Science

      Tom Froese

      A textbook-centered introduction to both the history of and state-of-the-art theorizing in embodied cognitive science. Through interactive group discussions, the course will explore key topics such as the machine metaphor of mind, perception and action, robotics and artificial life, cognitive technology, and consciousness. Book chapter selection will be tailored to the interests and backgrounds of the students.

      Prior knowledge

      Due to the highly interactive and group-based nature of the course, the number of students is limited to 9 and preference will be given to students with a background in one of the disciplines that form the cognitive sciences. Please consult with Prof Froese before enrolling.

      2 Term

      2 Credits

    8. B46 | Elective

      Introduction to Machine Learning

      Makoto Yamada

      Learn how to use machine learning methods for real data. Beginning with the basic of machine learning including linear algebra, probability, linear regression, and logistic regression, and progressing to deep learning methods. In addition to the lectures, hands-on classes develop competencies in practical use of these techniques. Finally, implement these in student-driven machine learning projects (possibly using data provided from OIST units).

      Prior knowledge

      We will teach about Python, basic linear algebra, and probability. However, prior knowledge of these topics is highly recommended.

      1 Term

      2 Credits

    9. B40 | Elective

      Introduction to Polymer Science

      Christine Luscombe

      Learn how polymers, widely used in everything from clothing to paints, drug delivery to electronics, function.  Discover which applications are appropriate for different polymers, and how polymers can be synthesized. Through classroom discussion, presentations, and journal club, explore the interrelationship between molecular structure, morphology, and properties, develop characterization techniques, and evaluate environmental impact and sustainability issues relating to polymers.

      Prior knowledge

      None.

      1 Term

      2 Credits

    10. B36 | Elective

      Introduction to Real Analysis

      Xiaodan Zhou

      An investigation into the mathematical foundations of calculus.  Through lectures and exercises, visit fundamental concepts of mathematical analysis including logic, basic set theory, functions, number systems, order completeness of the real numbers and its consequences, sequences and series, topology of R^n, continuous functions, uniform convergence, compactness, and theory of differentiation and integration.  Expand mathematical proof and writing skills through ample practice with LaTex to communicate mathematics effectively and demonstrate rigorous math thinking in preparation for more advanced courses.

       

      Prior knowledge

      The course is an introductory course and is designed to be accessible to students that are seeing proofs for the first time. The only prerequisite is an understanding of the results from single-variable calculus. Successful completion of undergraduate Calculus or equivalent courses is required to take this course. Multivariable calculus is not a prerequisite. If you are not sure about the prerequisite material, please contact the instructor at the beginning of the course.

      1 Term

      2 Credits

    11. B20 | Elective

      Introductory Evolutionary Developmental Biology

      Hiroshi Watanabe

      Survey the range of modern animal body plans, and discover how these have evolved through time. Examine the developmental process of multicellular organisms and how they have evolved through time, including specific molecular mechanisms at the genetic and cell signaling level. Learn about and use software and hardware techniques for researching development in animals. Discuss modern approaches and recent findings in the field through presentations and reports on specific issues in evolutionary developmental biology.  

      Prior knowledge

      No prior knowledge assumed

      2 Term

      2 Credits

    12. PD5 | Optional

      Laboratory Experience

      Students will be placed in a laboratory appropriate to their specific needs in terms of language and location.  They will participate in laboratory life on a full-time basis to learn the skills and techniques of that laboratory, to become familiar with laboratory behavior, and to receive training in scientific practice and routine.

      All Term

      1 Credits

    13. LRO | Mandatory

      Laboratory Rotations

      Course Requirements

      1. Prepare a written summary of the aims of the rotation. Students will study original publications and discuss with the Professor in charge of the research unit to prepare the aims. The summary should be no more than one page including references and illustrations. The proposal should be submitted to the graduate school (web form). Due date is the last day of the first calendar month of term.
      2. Undertake the activities in the research unit to fulfill the aims of the rotation. The activities should be completed during the term of the rotation.
      3. Participate in research unit meetings and seminars during the rotation. The student is expected to attend and as appropriate, ask questions, and join discussions.
      4. Present the results of the rotation activity as an oral presentation to the laboratory members. One of the three rotations will be presented as an oral presentation to the entire class as a part of Professional Development.
      5. Submit a written report on the rotation (web form). It is understood that results cannot be expected in so short a time, but the background, including a short literature review, methods used, and activity carried out in the research unit should be described using the scientific language of the field. The report is due on the last day of the final month of term. 
      6. Each student will do a minimum of three laboratory rotations, one per term.

      Selection of Rotations

      All students will undertake at least three rotations. Assignment of rotations is made by the Graduate School, following information provided by the student in the Academic Plan. Final approval of the selection of rotations will be given by the Dean, taking into account the availability of supervision and the overall program of the student. At least one of the rotations shall be outside the specific field of the student’s academic background.

      All Term

      Credits

    14. A107 | Elective

      Lie Algebras

      Liron Speyer

      Learn the fundamental objects in algebra, especially representation theory, with hands-on experience in computing representations and constructing sophisticated proofs for some powerful (and quite beautiful!) results. Practice focuses on the basic structures of simple Lie algebras over the complex numbers, as well as the theory of highest weight representation including Verma modules and enveloping algebras, concluding with Weyl's character formula for finite-dimensional simple modules. Additional topics include root systems, Cartan subalgebras, Cartan/triangular decomposition, Dynkin diagrams, and the Killing form.   

      This is an alternating years course.

      Prior knowledge

      A solid grasp of undergraduate linear algebra, as well as experience following long proofs and constructing your own proofs. Students must be very comfortable with proofs in order to understand the material in this course and complete the homework questions adequately. If you are unsure, please discuss this further with your academic mentor. Some prior knowledge of the representation theory of finite groups will also be helpful when grappling with analogous results for Lie algebras, but it is not completely necessary.  

      1 Term

      2 Credits

    15. B29 | Elective

      Linear Algebra

      Liron Speyer

      A rigorous mathematical introduction to linear algebra, directed at physics or engineering students, but also beneficial to neuroscientists and others who require linear and matrix algebra in their research.  Course assignments offer practice in working with linear maps between vector spaces, how these can be realised as matrices, and how this can be applied to solving systems of linear equations.  Topics include matrix operations, solving systems of linear equations, eigenvalues, eigenvectors, diagonalisation and Gram-Schmidt orthonormalisation. Not intended for mathematicians. 

       

      Alternating year course,  AY2023, AY2025

      Prior knowledge

      Familiarity with real and complex numbers.  Previous exposure to mathematical proofs strongly recommended.

      1 Term

      2 Credits

    16. A321 | Elective

      Macroevolution

      Lauren Sallan

      Macroevolution, or evolution above the population level and on long timescales, addresses fundamental questions regarding the origins of species, past and present. These include (but are not limited to): How are highly dissimilar species related? Why are animals on distant continents so similar? How and when did major groups, like arthropods or fishes, originate? What drives evolutionary arms races between predators and prey? Why are there so many more species of beetle than crocodile? Why are there more species in the tropics than the Arctic? Why do some animals survive mass extinction? How can invasive species spread so rapidly? Exploring these topics provides class participants with an opportunity to learn important concepts underlying our understanding of modern biodiversity and the fossil record. Using different methods and lines of evidence, including evolutionary trees (phylogeny), developmental and morphological observations, biodiversity and ecological databases, past climate and global events, biomechanics, mathematical modeling, and even data from modern genomics, they begin to answer essential questions about the evolution of life. This course will consist of lectures introducing concepts and methods followed by discussion sessions based on student questions and readings outside class.

      Prior knowledge

      Basic knowledge of and interest in biology or evolution assumed, undergraduate biology coursework preferred. Course B23 Molecular Evolution is required.  Contact Prof Sallan if you seek an exemption.

      2 Term

      2 Credits

    17. A102 | Elective

      Mathematical Methods of Natural Sciences

      Jonathan Miller

      An exploration and practicum in advanced mathematical techniques for application in the natural sciences.  The emphasis is on calculating physical quantities using analytical and numerical, exact and approximate methods. Instruction stresses calculational approaches rather than rigorous proofs with substantial practice in analytic calculation skills acquired via problem sets.  Examples and applications are drawn from a variety of fields.

      Prior knowledge

      Calculus,  e.g. A104 Vector and Tensor Calculus, or A108 Partial Differential Equations, Linear algebra, e.g., B29 Linear Algebra

      2 Term

      2 Credits

    18. A110 | Elective

      Measure Theory and Integration

      Xiaodan Zhou

      Explore foundational concepts of modern measure theory that  underpin advanced mathematical topics such as functional analysis, partial differential equations, and Fourier analysis.  Through lectures and exercises, investigate fundamental concepts of Lebesgue measure and integration theory and apply the definitions and properties of Lebesgue measure and measurable sets.  Discussion includes measurable functions, Lebesgue integrals, limit theorems of integrals, the Fubini theorem, and LP space. Using Latex for mathematical writing, hone mathematical proof and writing skills to communicate mathematics effectively and develop rigorous math thinking to prepare for more advanced courses.

      This is an alternating years course.

      Prior knowledge

      B36 “Introduction to Real Analysis” is recommended but not required. The following is expected prerequisite knowledge: basic set theory, mathematical logic, the fundamental property of real numbers; familiarity with limit definitions, and how to use these definitions in rigorous proofs of sequences, continuity and differentiation of real-valued functions; properties of a supremum (or least upper bound) and infimum (or greatest lower bound); basic topology including the definitions of open, closed, compact sets in the Euclidean space; basic definitions and properties of Riemann integrals. Please contact the instructor at the beginning of the course with questions.  

      1 Term

      2 Credits

    19. A319 | Elective

      Microbial Evolution and Cell Biology

      Filip Husnik

      Discover the vast genetic, cellular, and biochemical diversity of life that rests within single-celled organisms: the prokaryotes (bacteria and archaea) and microbial eukaryotes (protists). Through literature and laboratory exercises, explore the immense diversity of single-celled organisms (both prokaryotes and eukaryotes), focusing on their evolution, ecology, genetics, biochemistry, and cell biology, with a focus on the evolutionary history and major cellular innovations that occurred in single-celled organisms during the evolution of life.  Apply these insights to critically analyse research papers, design a research project, and write a grant application. In the laboratory, practice a range of techniques for studying cultured and field-sampled protists and prokaryotes, including microscopy and genomic approaches.

      Prior knowledge

      Basic understanding of evolutionary and cell biology at the undergraduate level is assumed. The following courses offered at OIST are recommended to students who first want to review their knowledge: Molecular Biology of the Cell (B27) and Evolution (B43) or Molecular Evolution (B23).

      1 Term

      2 Credits

    20. A212 | Elective

      Microfluidics

      Amy Shen

      Explore the interface between engineering and miniaturization, one of the most intriguing and active areas of inquiry in modern technology, through the interdisciplinary research area of microfluidics. Investigate emerging microfluidics disciplines, including molecular assembly to bulk and device level scales, and applications in novel materials synthesis, bio-technology and nanotechnology.  Learn about fundamental aspects of fluid mechanics, scaling laws and flow transport at small length scales with case studies in multi-phase flows, droplet-based microfluidics along with capillary-driven, pressure-driven, and electro-kinetic based microfluidics.  Perform hands-on lab experiments on standard microfabrication techniques and lab-on-a-chip device integration.

      Prior knowledge

      A good pass in B13 Fluid Mechanics is required for A212. If you have taken Fluid Mechanics during your former BSc or MSc degree, please contact Prof. Amy Shen directly to determine whether you are prepared to take A212.

      3 Term

      2 Credits

    21. B27 | Elective

      Molecular Biology of the Cell

      Keiko Kono

      Survey the molecular biology of the cell, the universal biochemical mechanisms at the heart of all living organisms, through lectures based on the classic text by Alberts et al.  Working through research-based problem sets, explore the cell and its components and constituents from the level of individual molecules to their interaction, dynamics and control at the cellular and intercellular level.  Classroom discussions explore new findings that may challenge previous conclusions.

       

       

      Prior knowledge

      No assumed knowledge. The course is very basic. Non-biology students are welcome. 

      1 Term

      2 Credits

    22. B23 | Elective

      Molecular Evolution

      Tom Bourguignon

      Recent advances in technology and software for analysis of genetic sequences have rapidly expanded our understanding of the process of evolution at the molecular level. Learn about the basic concepts of molecular evolution, and how they contribute to evolution on larger scales. Use modern tools for gene sequencing to determine changes in genes and their resulting protein changes, and discuss the impact of these on the biology of organisms. Learn how to use a number of widely-used bioinformatics tools for gene annotation, orthology, constructing phylogenetic trees, and genomics and proteomics. Apply these tools to answer important questions in biology such as the evolution of species. Explore the use of modern genetic sampling and sequencing tools and techniques in the analysis of environmental and ancient DNA.

      Prior knowledge

       Assumes general knowledge in biology  

      3 Term

      2 Credits

    23. A307 | Elective

      Molecular Oncology and Cell Signalling

      Tadashi Yamamoto

      Explore recent progress in cancer research and the mechanism of tumor development (carcinogenesis) from molecular and cellular functions of oncogenes and anti-oncogenes. Through readings, recent research papers, and hands-on exercises, gain insights into the relevance of genome sciences and systems biology to cancer research. Study the contributions and relevance of signal transduction, cell cycle progression, cell adhesion, and gene regulation to tumor development and discuss animal models of cancer and modes of treatment and drug development. Visiting speakers provide insight into various advanced topics.

      Prior knowledge

      Requires at least advanced undergraduate level Cell Biology and Genetics or similar background knowledge

      2 Term

      2 Credits

    24. A314 | Elective

      Neurobiology of Learning and Memory I

      Jeff Wickens

      The aim of this course is to engage students in thinking about and discussing fundamental issues in research on neural mechanisms of learning and memory. Topics include the neural mechanisms of learning, memory, emotion, and addictive behavior. Students will be expected to read original reports including classical papers as well as recent advances. The course includes an experimental requirement in which students must design and conduct an experiment related to learning and memory mechanisms of the brain.

      Prior knowledge

      Students should have previously taken at least two basic courses in neuroscience or have completed the equivalent by documented prior learning 

      3 Term

      2 Credits

    25. A318 | Elective

      Neurobiology of Learning and Memory II

      Kazumasa Tanaka

      Learn fundamental neural mechanisms of learning and memory, with a focus on memory. Through lectures and journal club presentations, discover connections between synaptic plasticity and memory, and the important role of the hippocampus in different types of memory. Compare and contrast synaptic and systems consolidation mechanisms of memory, and their effects and consequences. Apply this knowledge in preparing a mock grant proposal for a significant question in memory research.

      Prior knowledge

      Students interested in memory and should have basic knowledge of neuroscience.

      3 Term

      2 Credits

    26. A306 | Elective

      Neuroethology

      Yoko Yazaki-Sugiyama

      Explore the neuronal mechanisms that underlie and control complex animal behavior.  Learn about sensory processing mechanisms responsible for behaviors such as echolocation and sensory navigation.  Learn about motor control mechanisms such as central motor pattern generators, stereotyped behavior, and spatial navigation. Discuss the evolutionary strategy and the biological ideas of animal behavior and underlying neuronal mechanisms, including sexually dimorphic behavior, behavioral plasticity, learning and memory, and the critical period. Critically analyze original research papers and literature to provide an understanding of modern experimental techniques in neuroethology.  

      Prior knowledge

      Requires introductory neuroscience course or equivalent.

      1 Term

      2 Credits

    27. B24 | Elective

      Neuromotor Systems

      Marylka Yoe Uusisaari

      The course will start from the mechanisms of animal movement, including the evolutionary, ecological and energetic aspects; we will explore the anatomical and mechanical features of the body machinery (such as muscles, bones and tendons) before investigating the structure and dynamic function of the neuronal circuits driving and controlling movements. We will thus examine neuronal function at various levels, allowing the students to familiarize themselves with many fundamental concepts of neuroscience; the theoretical lectures will be complemented by practical exercises where the students will study movement in themselves and their peers in the motion capture laboratory environment as well as with more classical approaches. 

      Prior knowledge

      This is a basic level course, which will be adjusted according to the interests of enrolled students. No prior knowledge assumed, and suitable for out-of-field students.  However, an Introductory Neuroscience course is required if you intend to continue with additional Neuroscience courses.

      1 Term

      2 Credits

    28. A316 | Elective

      Neuronal Molecular Signaling

      Marco Terenzio

      Review receptor signaling and its associated signaling cascades and transcriptional responses as well as peripheral local translation of signaling molecules. Discuss the mechanisms of active transport utilized by the neurons to convey organelles and signaling complexes from the plasma membrane to the nucleus, with a focus on the dynein machinery and retrograde axonal transport. Learn about links between defects in axonal trafficking and neurodegenerative diseases and between local translation of the response to axonal injury and the induction of a regenerative program, in both peripheral and central nervous systems. In the laboratory, learn and use the most recent techniques for neuronal cell culture and the live imaging and quantifying of intracellular transport. Journal clubs develop critical analysis of recent research papers in the field of molecular neuronal signaling and anterograde/retrograde messenger transport.

      This course is targeted to students who want to deepen their understanding of neuronal axonal signaling and get some hands-on experience in intracellular trafficking live imaging.

      The aim of this course is to discuss some of the major molecular signaling pathways from the periphery to the cell bodies in neurons. The students are expected to achieve a basic understanding of long-range molecular signaling in neurons and the experimental techniques available for its investigation.

      Prior knowledge

      This course is an advanced course for neuroscience. It assumes a basic knowledge of cellular biology and neurobiology.

      3 Term

      2 Credits

    29. A220 | Elective

      New Enzymes by Directed Evolution

      Paola Laurino

      Discover and apply a range of technologies and techniques to generate, isolate, and enhance mutated bacterial proteins. Lectures and readings about protein structure, function and evolution are complemented by an extensive laboratory project in directed protein evolution that develops applicable research skills.  Special topics in protein engineering include gene mutations, ancestral protein reconstruction, and rational design of new enzymes. Explore additional topics by journal club and student presentations.

      Prior knowledge

      Undergraduate level biochemistry or molecular biology.

      2 Term

      2 Credits

    30. A105 | Elective

      Nonlinear Waves: Theory and Simulations

      Emile Touber

      Many physical processes exhibit some form of nonlinear wave phenomena. However diverse they are (e.g. from engineering to finance), however small they are (e.g. from atomic to cosmic scales), they all emerge from hyperbolic partial differential equations (PDEs). This course explores aspects of hyperbolic PDEs leading to the formation of shocks and solitary waves, with a strong emphasis on systems of balance laws (e.g. mass, momentum, energy) owing to their prevailing nature in Nature. In addition to presenting key theoretical concepts, the course is designed to offer computational strategies to explore the rich and fascinating world of nonlinear wave phenomena.

      Whilst the course is aimed at graduate students with an engineering/physics background, biologists interested in wave phenomena in biological systems (e.g. neurones, arteries, cells) are also welcome. 

       

      Prior knowledge

       Prior knowledge of mathematics for engineers and physicists.

      2 Term

      2 Credits

    31. A214 | Elective

      Nucleic Acid Chemistry and Engineering

      Yohei Yokobayashi

      Learn basic principles of nucleic acid chemistry and engineering through lectures and discussions. Build on this basic knowledge to explore current research in the field of nucleic acid chemistry and engineering. Emphasis will be placed on discussing current and future applications of nucleic acids in diverse fields including chemistry, biology, materials, medicine, biosensors, and engineering through current literature. Depending on the number of students and availability of resources, either development of a research proposal or a short laboratory session will be performed.

      Prior knowledge

      Assumes undergraduate organic chemistry or biochemistry.

      2 Term

      2 Credits

    32. B33 | Elective

      Organic Photonics and Electronics

      Ryota Kabe

      Explore the exciting interdisciplinary world of organic photonic and electronic devices, with wide application in industry and research. Lectures and accompanying hands-on experiments develop understanding of fundamental concepts in synthesis and  purification of organic optoelectronics. Perform a range of photophysical functional analyses. Discover and discuss device physics and fabrication of organic LEDs, transistors, solar cells, and lasers.

      Prior knowledge

      Undergraduate level chemistry. 

      1 Term

      2 Credits

    33. A108 | Elective

      Partial Differential Equations

      Qing Liu

      Through lectures and assignments, explore a variety of PDEs with emphasis on the theoretical aspects and related techniques to find exact solutions and understand their analytic properties.  Learn both basic concepts and modern techniques for the formulation and solution of various PDE problems.  Main topics include the method of characteristics for first order PDE, formulation and solutions to the wave equation, heat equation and Laplace equation, and classical tools to study properties of these PDEs.

      Prior knowledge

      Single-variable and multi-variable calculus, linear algebra, ordinary differential equations, real analysis, or equivalent knowledge.

      3 Term

      2 Credits

    34. A115 | Elective

      Partial Differential Equations II

      Ugur Abdulla

      Learn modern theory of partial differential equations (PDEs) with emphasis on linear and nonlinear PDEs arising in various applications such as mathematical physics, fluid mechanics, mathematical biology and economics. Explore topics including Sobolev spaces and their properties, second order elliptic, parabolic and hyperbolic PDEs, concept of weak differentiability, weak solutions, Lax-Milgram theorem, energy estimates, regularity theory, Harnack inequalities, topics on nonlinear PDEs.

      Prior knowledge

      Functional Analysis and A108-Partial Differential Equations, or its equivalent.

      2 Term

      2 Credits

    35. B08 | Elective

      Physics for Life Sciences

      Bernd Kuhn

      Principles of physics of central relevance to modern biological analysis and instrumentation are introduced with an emphasis on application in practical research areas such as electrophysiology, optogenetics, electromagnetics, the interaction of light and matter, and brain recording, stimulation, and imaging.

      2 Term

      2 Credits

    36. A315 | Elective

      Quantifying Naturalistic Animal Behavior

      Sam Reiter

      Naturalistic animal behavior is complex. Learn the practical skills of how to record and track this complex behavior using modern tools, and the pros and cons of different approaches. Discuss recent work on modeling individual and collective animal behavior while maintaining quantitative rigor, as well as the relationship between behavior and the brain. Investigate connections between behavior and neural activity in the model animal systems of nematode, fruitfly, squid, and mouse. Read and assess papers weekly. Design and complete a short project in studies of complex behavior, with support from relevant literature. Present the results of the project to the class.

      Prior knowledge

      Introductory neuroscience and preparation in one or more areas of linear algebra, machine learning, or behavioral ecology is recommended.

      3 Term

      2 Credits

    37. A227 | Elective

      Quantum Engineering – Simulation and Design

      Jason Twamley

      Develop skills in the computational modelling of quantum machines and integrated quantum devices used for fundamental quantum mechanics studies, quantum sensing, quantum communication and quantum computing.  Use  “engineering” style skills to design and model – theoretically and computationally – various composite quantum devices: integrated photonic with atomic, condensed matter and motional atomic systems including cavity quantum electrodynamics, cavity optomechanics, Nitrogen vacancy defects in diamond, and levitated quantum systems.  Learn and use computational techniques to simulate the properties of integrated quantum devices using python, with a final computational project. Discuss the latest literature in journal club style.

      Prior knowledge

      Undergraduate quantum mechanics (full year) is required. This includes good knowledge of the quantum matrix mechanics for spin, Schrodinger equation (stationary and time dependent), and the operator treatment of the quantum harmonic oscillator including creation and annihilation operators. Desirable pre-knowledge includes cavity quantum electrodynamics and atoms interacting with electromagnetic radiation. Introductory level Python is also required.

      3 Term

      2 Credits

    38. A205 | Elective

      Quantum Field Theory

      Shinobu Hikami

      Learn quantum field theory from lectures and by working through classic and recent papers to follow developments in the field.  Progress from a reconsideration of basic concepts in quantum effects acting on electrons and other particles, through to Feynman rules and diagrams, and Weyl and Dirac spinors.  Develop these concepts into gauge theories, field quantization, symmetry breaking, and renormalization.  Finally consider quantum chromodynamics, gravity and nuclear forces, and possibilities to unified field theory including strings.  Confirm these findings through homework exercise sets and a final examination. Due to recent developments, an emphasis is placed on random matrices and knot theory, topological field theory, and applications to topological insulators.

      Prior knowledge

      Solid undergraduate electrodynamics and quantum mechanics preparation.  

      3 Term

      2 Credits

    39. A231 | Elective

      Quantum Information and Communication Theory

      David Elkouss

      A thorough initiation into the fundamental aspects of quantum communications. The course is divided into four blocks. It begins with an introduction to data compression and communication over noisy channels in classical information theory. The second part discusses quantum entropies, distance measures between quantum states and quantum data compression. The third part of the course introduces quantum channels, and derives the fundamental properties for communications over quantum channels. The course ends with an in-depth introduction to quantum key distribution including its security proof.

      Prior knowledge

      Linear algebra, probability and statistics. The student will benefit from introductory knowledge on quantum information, though the exposition will include a short introduction to quantum bits, operations and measurements.

      2 Term

      2 Credits

    40. A228 | Elective

      Quantum Many-Body Physics

      Philipp Höhn

      Explore the interface of condensed matter physics, quantum information theory and high-energy physics, a highly active area of current research, through the lens of quantum many-body physics. Study correlation structures and their role in determining the physical properties of these systems. Understand the special role of ground states and their entanglement properties, such as entanglement area laws and how correlations decay over distance. Learn how to sidestep the complexity of many-body systems and efficiently describe their properties using approximation tools, such as tensor networks and several renormalization methods that have become standard workhorses in the modern literature. Review standard phase transitions and find out how symmetries lead to a novel notion of symmetry protected phases and topological phase transitions. Time permitting, discover how to compute entanglement entropies in the presence of gauge symmetries and in quantum field theory. Practice these findings in exercises and journal club presentations and explain them in a final oral exam. 

      Prior knowledge

      Basic Quantum Mechanics and ideally Advanced Quantum Theory. A further background in Quantum Field Theory and Statistical Physics is helpful.

      1 Term

      2 Credits

    41. A223 | Elective

      Quantum Materials Science

      Yoshinori Okada

      Discover a range of interesting quantum materials and their unique functionalities. Learn about the concept of materials design and its realization in bulk single crystal growth and epitaxial thin film growth. Learn the principles of single particle spectroscopy, particularly focusing on photoemission and tunneling spectroscopy. Experience quantum materials growth and characterization in the laboratory. Discuss and make presentations on recent literature. 

      Prior knowledge

      Undergraduate level of condensed matter physics

      3 Term

      2 Credits

    42. A230 | Elective

      Quantum Optics for Qubits

      Hiroki Takahashi

      Work from basic notions of quantum optics to prepare a theoretical foundation that facilitates understanding of the working principles of modern quantum devices, such as linear optical quantum computers, ion traps, and superconducting circuits. Describe physical systems used in quantum technology applications by simple quantum physics of spins (two level systems) and harmonic oscillators.   Solve dynamics of quantum systems using master/Schroedinger equations.  Explain working principles of important quantum devices and protocols such as cavity QED, quantum input-output relation, two-qubit entangling gates, ion traps, Josephson junctions, and some circuit QED.  Critically analyze and make presentations on important literature in the field, and demonstrate understanding of quantum optics through regular problem sets.

      Prior knowledge

      Undergraduate-level quantum mechanics and linear algebra

      3 Term

      2 Credits

    43. A221 | Elective

      Relativistic Mechanics and Classical Field Theory

      Yasha Neiman

      We begin with a gentle and thorough introduction to Special Relativity, and take some time to have fun with shapes in Minkowski space. We proceed to an advanced treatment of relativistic particles, electromagnetic fields and weak gravitational fields (to the extent that doesn’t require General Relativity). Antiparticles are introduced early on, and we put an emphasis on actions and phase space structures. We introduce the geometric concept of spinors, and the notion of spin for particles and fields. We discuss the Dirac equation and the resulting picture of the electron. We introduce conformal infinity. Time allowing, we discuss a bit of conformal field theory and some physics in de Sitter space. 

      Prior knowledge

      Maxwell’s equations in differential form. Solving Maxwell’s equations to obtain electromagnetic waves. Quantum mechanics.   

      1 Term

      2 Credits

    44. A312 | Elective

      Sensory Systems

      Izumi Fukunaga

      The course will cover general concepts and specific sensory modalities. Classes alternate between lecture-style teaching and a journal club. Each lecture will be based on a textbook chapter (including Kandel et al.’s Principles of Neural Sciences) to cover basic and broad topics, but will also serve as an opportunity to introduce concepts required to understand the research article associated with the lecture.

      The course is structured for students who would like to know about sensory systems in the brain at an advanced level. The overall aim is expose students to research-level materials, but starting from basic concepts. Topics will include specialisations as well as common principles found in the mechanisms of sensory perception, and will cover the somatosensory, visual, auditory, olfactory systems from transduction to higher cognitive functions. In parallel, the course aims to develop students’ ability to read and discuss primary research articles, to give students an exposure to some of the latest techniques and developments.

      Prior knowledge

      The course is aimed at students with a background in neuroscience (either at the BSc/MSc level or having successfully completed some of the basic neuroscience courses offered at OIST). It assumes knowledge in cellular neurophysiology and neuroanatomy. 

      3 Term

      2 Credits

    45. SPT | Elective

      Special Topics

      The course Special Topics will provide an opportunity for students to study topics concerning recent scientific breakthroughs, cutting edge research of topical interest, novel, state of the art technologies, and techniques not otherwise available, with leading international experts in those topics or technologies.  

      This course option must be conducted in collaboration with a faculty member to provide internal academic oversight and guidance, and will follow common guidelines to ensure the required academic standards are maintained. 

      Each Special Topics course will require the approval of the Dean before being offered.  

      Students will be required to obtain the approval of the Academic Mentor or Thesis Supervisor before taking the course, and complete a defined piece of work as part of the course. 

      All Term

      1 Credits

    46. A229 | Elective

      Statistical Fluctuations and Elements of Physical Kinetics

      Denis Konstantinov

      Explore and explain key ideas of physical kinetics, for systems both at equilibrium and then driven out of equilibrium by a variety of factors.  Derive the very important relation (FDT) between fluctuations and dissipation in a dynamic system coupled to a noisy environment. Describe (within certain approximations) the dynamics of classical systems driven out of equilibrium. Apply models and equations to quantify the transport properties of some idealized solid-state and condensed-matter systems. Extend some of these ideas to quantum systems, in particular those interacting with an environment, and explore the dynamics of dissipative ("open") quantum systems.  Develop an intuitive understating of the physical picture rather than pursuing a rigorous mathematical description of the phenomena with numerous examples and model problems from solid state and condensed matter physics, atomic physics, and quantum optics, and reinforce these with regular problem sets.

      Prior knowledge

      Statistical Physics (B12) or Statistical Mechanics, Critical Phenomena and Renormalization Group (A225); anything equivalent to a basic course on Nonrelativistic Quantum Mechanics.

      2 Term

      2 Credits

    47. A225 | Elective

      Statistical Mechanics, Critical Phenomena and Renormalization Group

      Reiko Toriumi

      An introduction to the methods of statistical mechanics that evolves into critical phenomena and the renormalization group.
      The analogy between statistical field theory and quantum field theory is addressed throughout the course.
      The key concept emphasized in this course is universality; we are concerned with systems with a large number of degrees of freedom which may interact with each other in a complicated and possibly highly non-linear manner, according to laws which we may not understand. However, we may be able to make progress in understanding the behavior of such problems by identifying a few relevant variables at particular scales. The renormalization group addresses such a mechanism.
      Some selected topics are covered, such as conformal field theory, vector models/matrix models, and SLE.

      Prior knowledge

      Classical Mechanics and Quantum Mechanics to advanced undergraduate level

      1 Term

      2 Credits

    48. B32 | Elective

      Statistical Modeling

      Tomoki Fukai

      Learn the mathematical methods to analyze high-dimensional data for statistical inference. Use large data sets to construct a statistical model that not only describes the dataset but also allows for prediction of future data. Progress from simple regression models through more sophisticated techniques for dimensional reduction, categorization, and decision making.  Use Bayesian approaches  and clustering techniques as an introduction to machine learning. Weekly exercises and homework consolidate this learning.

      This course provides an introduction to machine learning.   Students are required to have some knowledge and skills in mathematics. However, the course is not intended for pure theorists.

      This course can be taken immediately after the course B31 Statistical Testing, or as a stand-alone course.

       

      Prior knowledge

      Basic knowledge and skills in linear algebra (matrix, eigenvalues, eigenvectors, etc.), calculus (differentiation and integration of functions), and probability theories (Gaussian and some other distributions) are required. Skills in Python programming are also required for exercises.

      2 Term

      1 Credits

    49. B12 | Elective

      Statistical Physics

      Nic Shannon

      Explore why matter can exist in more than one phase, and how it can transform from one phase into another.  Develop the ideas of entropy, free energy and thermal equilibrium starting from the question “what is temperature?”.  From the context of thermodynamics, and as natural consequences of a statistical description of matter, develop a simple physical picture of phase transitions with an emphasis on the unifying concept of broken symmetry.  Demonstrate understanding of the subject through weekly problem sets, and deliver a final presentation on a modern example of the application of statistical physics ideas, chosen by the student.  Accessible to students from a wide range of education backgrounds.

      Prior knowledge

      Undergraduate calculus and algebra.

      2 Term

      2 Credits

    50. B31 | Elective

      Statistical Tests

      Tomoki Fukai

      Develop the basic methodology of hypothesis testing for statistical analysis of experimental and simulation studies. Through lectures and exercises using Python, explore the fundamentals of probability theory, population statistics, and statistical methods including p-values, t-test, U-test, Welch test, confidence intervals, single and multivariate analyses, and correlations. Extend these concepts with discussion of information theory, mutual information, and experimental design. 

      Students who have not learned the basics of statistical methods and will conduct experimental studies or numerical simulations in the future are encouraged to take the course.

      Prior knowledge

      Students are expected to have basic knowledge of elementary mathematics such as differentiation, integration, and elementary linear algebra. However, whenever necessary, mathematical details will be explained. Students will need to write some code in Python.

      2 Term

      1 Credits

    51. B44 | Elective

      Stellar Physics

      Shigehiro Nagataki

      Explore the mysteries of astrophysics by delving into the physics of the lifecycle of stars, including the Sun, massive stars, white dwarfs, supernovae explosions, and supernova remnants. Through lectures and hands-on activities, learn how to use physical modeling to determine distances between celestial objects, their age and other key characteristics, and thereby gain insights into the structure of the universe filled with dark matter and dark energy. 

      Prior knowledge

      Fundamental undergraduate-level physics recommended but not required.

      1 Term

      2 Credits

    52. A103 | Elective

      Stochastic Processes with Applications

      Simone Pigolotti

      A broad introduction to stochastic processes, focusing on their application to describe natural phenomena and on numerical simulations rather than on mathematical formalism.  Define and classify stochastic processes (discrete/continuous time and space, Markov property, and forward and backward dynamics). Explore common stochastic processes (Markov chains, Master equations, Langevin equations) and their key applications in physics, biology, and neuroscience. Use mathematical techniques to analyze stochastic processes and simulate discrete and continuous stochastic processes using Python.

      Prior knowledge

      Calculus, Fourier transforms, probability theory, scientific programming in Python.

      3 Term

      2 Credits

    53. B30 | Elective

      Surface Sciences

      Yabing Qi

      Discover the fundamental properties of physics and chemistry occurring at surfaces and interfaces, central to many recent developments in  science and technology, such as physical chemistry, electronic devices, catalysis, semiconductor processing, new materials development, biomaterials, biotechnology and biomedicine, nanotechnology, and others. Through lectures, projects, and assignments, learn the basic concepts of the field, and operation principles of major analytical techniques and instruments, such as scanning tunneling microscopy (STM), atomic force microscopy (AFM), X-ray photoelectron spectroscopy (XPS), and ultraviolet photoemission spectroscopy (UPS). Discuss the applications of these concepts and instruments in various research fields.

      Prior knowledge

      General knowledge in physics and chemistry.

      2 Term

      2 Credits

    54. A226 | Elective

      Synthetic Chemistry for Carbon Nanomaterials

      Akimitsu Narita


      Learn classical and modern approaches in the organic synthesis of molecular nanocarbons and related compounds, with a focus on large polycyclic aromatic hydrocarbons that are also recently called nanographenes. Explore the relationship between their structures and optical, electronic, and magnetic properties along with related analytical techniques. Discover relevant methods in polymer chemistry and surface sciences for synthesis and characterization of graphene nanoribbons and other carbon nanostructures. Discuss the latest developments in the related research areas in class presentations. 

      Prior knowledge

      Undergraduate-level general chemistry; Advanced-level organic chemistry.

      3 Term

      2 Credits

    55. A320 | Elective

      The Cell Cycle and Human Diseases

      Franz Meitinger

      Cell division is the key to life. We all started out as a single cell, which divided billion of times to form an organism with complex tissue structures and the ability to think, create and learn. Defects in cell division are often fatal at an early stage of human development. Mutations in the germline can lead to genetic disorders that impair physical and mental abilities such as microcephaly or DNA repair-deficiency disorders, which increase the predisposition for diseases that occur later in life. On the other hand, mutations in dividing somatic cells can lead to genome instability, which is a hallmark of cancer. Many of the above-mentioned diseases are related to defects in the cell cycle, which coordinates genome and cell organelle duplication with cell division. Main topics of this course include genetic disorders that are related to mechanisms of cell division and are discussed using primary literature. Central elements of the cell division machinery and disease-causing defects are investigated in the laboratory using fluorescent imaging of living cells in combination with clinically relevant drugs and protein-specific chemical inhibitors.

      Prior knowledge

      Required: Basic knowledge of molecular biology and genetics. Recommended complementary courses: Molecular Oncology and Cell Signaling (Prof. Yamamoto); Molecular Biology of the Cell (Prof. Kono) and Modern Genetic Technologies (Prof. Kiyomitsu)

      2 Term

      2 Credits

    56. B42 | Elective

      The Diversity of Fish

      Vincent Laudet

      Learn about the rich diversity of fish and the incredible array of traits, behaviors, and survival mechanisms they display. Through lectures, projects, and discussions, use the diversity of fish to examine how they interact with, and are shaped by, their diverse environments. Integrate results from the scientific disciplines of ecology, physiology, and biophysics and explore the value and limits of biological models. Conduct a bibliographical research project that uses viewpoints from several scientific disciplines to solve a biological question about a species of fish, and present your findings.

      1 Term

      2 Credits

    57. A224 | Elective

      The Earth System

      Satoshi Mitarai


      Learn how climate and climate change are driven by interactions between the ocean and the atmosphere, the two key components of the Earth system.  Discuss global energy balance, atmospheric circulation, surface winds and ocean circulation, deep-sea thermohaline circulation, Holocene climate, the El Niño Southern Oscillation, projections of future atmospheric CO2 and other greenhouse-gas concentrations, and the effects of climate change on marine environments. Create, analyze, and present predictions using the latest atmosphere-ocean coupled general circulation models (CMIP) to assess potential effects of climate change on ocean-atmosphere systems. Explore past global changes and those anticipated in the future due to anthropogenic carbon releases, based upon IPCC future climate change scenarios and past climate records.  Develop tools to describe the influence of climate change on ocean environments quantitatively, and to consider potential outcomes for marine ecosystems on which students' own research is focused.

      Prior knowledge

      Vector calculus, boundary problems, differential equations, and coding ability required.

      3 Term

      2 Credits

    58. B13 | Elective

      Theoretical and Applied Fluid Mechanics

      Pinaki Chakraborty

      Explore a wide spectrum of flows from nature to engineering while learning the basic concepts, equations, and methods of fluid mechanics.  Consider conservation laws and constitutive equations, derive the Navier-Stokes equations, and interpret exact and approximate solutions.  Discussion includes an introduction to the theory of hydrodynamic stability and turbulent flows.  

      Prior knowledge

      Prerequisite is A104 Vector and Tensor Calculus, or equivalent. B10 Analytical Mechanics, or equivalent.

      2 Term

      2 Credits

    59. B14 | Elective

      Theoretical and Applied Solid Mechanics

      Gustavo Gioia

      An introduction to the basic concepts, equations, and methods of the mechanics of solids, including solutions of representative problems in linear elasticity.   Through lectures and  reading exercises, discover the concepts of stress and strain, and discuss conservation laws and constitutive equations.  Derive the Navier equations of linear elasticity, and use them and the Airy stress-function method to understand the mechanics of fracture and of plastic deformation.  Solve problems to illustrate the behavior of cracks, dislocations, and force-induced singularities in applications in materials science, structural engineering, geophysics, and other disciplines.  

      Prior knowledge

      Prerequisite is A104 Vector and Tensor Calculus. Requires undergraduate-level knowledge of calculus and differential equations.

      3 Term

      2 Credits

    60. LTP | Mandatory

      Thesis Proposal

      Students work in the laboratory of the Professor under whom they wish to conduct their thesis research. They undertake and write up preliminary research work, complete an in-depth literature review and prepare a research plan. The preliminary research work should include methods the students will use in their thesis research. The literature review should be in the area of their thesis topic and be of publishable quality. The research plan should comprise a projected plan of experiments to answer a specific question(s) and place the expected outcomes against the current state of knowledge, and should take into account the resources and techniques available at OIST. The research data generated in this proposal may be included in the subsequent doctoral thesis, if appropriate.

       

      All Term

      Credits

    61. A273 | Elective

      Ultracold Quantum Gases

      Thomas Busch

      The course will start out by introducing the fundamental ideas for cooling and trapping ultracold atoms and review the quantum mechanical framework that underlies the description of interacting matter waves in the ultracold regime. This will introduce the idea of degenerate Bose and Fermi gases, and in particular the concept of Bose-Einstein condensation.

      After this the main properties of Bose-Einstein condensates will be discussed, including coherence and superfluidity, and for Fermi gases the physics of the BCS transition will be introduced. Conceptually important developments such as optical lattices, Feshbach resonances, artificial gauge fields and others will be explained in detail as well. New developments in the area of strongly correlated gases will be introduced and applications of cold atoms in quantum information or quantum metrology provide the final part of the course.

      The course will mostly focus on the theoretical description of ultracold quantum gases, but regularly discuss experimental developments, which go with these.

       

      Prior knowledge

      While the fundamental concepts of atomic physics and quantum mechanics that are required will be reviewed in the beginning of the course, basic prior knowledge of quantum mechanics is required (e.g. undergraduate quantum mechanics). Companion course to A211 Advances in Atomic Physics

      2 Term

      2 Credits

    62. A209 | Elective

      Ultrafast Spectroscopy

      Keshav M. Dani

      Discover and use the techniques of ultrafast spectroscopy with an overview of modern methods and applications. Through exercises and presentations, explore the basic concepts underlying sub-picosecond phenomena in nature (ultrafast chemical processes, femtosecond electron dynamics in materials, etc.) and the tools used to study such phenomena (pump-probe spectroscopy, Terahertz time domain spectroscopy, etc.).  Use these tools and techniques to perform measurements in the laboratory. Confirm these concepts through regular exercise sets and a final presentation.

      3 Term

      2 Credits

    63. A104 | Elective

      Vector and Tensor Calculus

      Eliot Fried

      A geometrically oriented introduction to the calculus of vector and tensor fields on three-dimensional Euclidean point space, with applications to the kinematics of point masses, rigid bodies, and deformable bodies. Aside from conventional approaches based on working with Cartesian and curvilinear components, coordinate-free treatments of differentiation and integration will be presented. Connections with the classical differential geometry of curves and surfaces in three-dimensional Euclidean point space will also be established and discussed.

      Prior knowledge

      Multivariate calculus and linear (or, alternatively, matrix) algebra.

      1 Term

      2 Credits

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    Bandi

    OIST Faculty