Courses

Please click the course number (first column) for detailed information including prerequisites.

The course schedule may change every year. Please check the timetable for the latest information.

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Course Sort descending Title Term Credits Course Coordinator Prerequisites or Prior Knowledge Notes
A103 Stochastic Processes with Applications 3 2 Simone Pigolotti

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

Students must install the Jupyter notebook
A104 Vector and Tensor Calculus 1 2 Eliot Fried

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

Alternate years course, odd years alternates with A112
A105 Nonlinear Waves: Theory and Simulation 2 2 Emile Touber

Mathematics for engineers and physicists

A106 Computational Mechanics 3 2 Marco Edoardo Rosti

Partial differential equations.
Some knowledge of Python, MATLAB or other language is preferred.

A107 Lie Algebras 1 2 Liron Speyer

Solid undergraduate linear algebra. Confident in following and constructing proofs. Some prior knowledge of the representation theory of finite groups is helpful but not completely necessary. Discuss this carefully with your academic mentor.

Alternate years course: AY2024
A108 Partial Differential Equations 3 2 Qing Liu

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

A110 Measure Theory and Integration 1 2 Xiaodan Zhou

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.

Alternate years course: AY2025
A111 Nonlinear Time Series Analysis and Manifold Learning 3 2 Gerald Pao

Python and/or R programming, linear algebra, B49 Dynamical systems

Alternate years course: AY2023
A112 Introduction to the Calculus of Variations 2 2 Eliot Fried

Students should have a robust understanding of undergraduate-level calculus, single and multivariable. Familiarity with differential equations would also be beneficial.

Alternate years course, even years alternates with A104
A113 Brain Computation 3 2 Kenji Doya

Programming in Python, e.g B50 Introduction to Scientific Computing. Basic knowledge in neuroscience, e.g. B52 Introduction to Neuroscience or A310 Computational Neuroscience, and statistical machine learning, e.g B46 Introduction to Machine Learning or B1 Statistical Tests, is preferred.

A114 Functional Analysis 1 2 Xiaodan Zhou

Single-variable and multi-variable calculus, linear algebra, B36 Real Analysis, A110 Measure Theory, or equivalent.

Alternating Years Course, odd years
A115 Partial Differential Equations II 2 2 Ugur Abdulla

A114 Functional Analysis and A108 Partial Differential Equations, or equivalent.

A121 Nonlinear Time Series Analysis and Manifold Learning Laboratory 1 2 Gerald Pao

Required pass in first theoretical portion of this course, A111 Nonlinear Time series Analysis and Manifold Learning.
Prior deep knowledge of Taken’s theorem-based methods is an absolute prerequisite.

Follow-on course from A111 (required)
A203 Advanced Optics 2 2 Síle Nic Chormaic

Quantum Mechanics

Alternate years course: AY2024 Enrollment cap of 8 students
A205 Quantum Field Theory 3 2 Shinobu Hikami

Quantum Mechanics and B11 Classical Electrodynamics

Course retires AY2023
A208 Bioorganic Chemistry 2 2 Fujie Tanaka

Undergraduate organic chemistry and/or biochemistry or related chemistry

A209 Ultrafast Spectroscopy 3 2 Keshav M. Dani

B11 Classical Electrodynamics, A203 Advanced Optics

Enrollment cap of 8 students
A211 Advances in Atomic Physics 2 2 Síle Nic Chormaic

Quantum Mechanics

companion course to A203 Advanced Optics

Alternate years course, AY2025 Enrollment cap of 8 students
A213 Inorganic Electrochemistry 1 2 Julia Khusnutdinova

Undergraduate chemistry

A214 Nucleic Acid Chemistry and Engineering 2 2 Yohei Yokobayashi

Assumes undergraduate organic chemistry or biochemistry.

A218 Condensed Matter Physics 2 2 Yejun Feng

Basic quantum mechanics and basic concepts of statistics.

A219 General Relativity 1 2 Yasha Neiman

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

Alternate years course, AY2025
A220 New Enzymes by Directed Evolution 2 2 Paola Laurino

Undergraduate level biochemistry or molecular biology

Enrollment cap of 8
A221 Relativistic Mechanics and Classical Field Theory 1 2 Yasha Neiman

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

Alternate years course, AY2024
A223 Quantum Materials Science 3 2 Yoshinori Okada

Undergraduate level of condensed matter physics

A224 The Earth System 3 2 Satoshi Mitarai

Undergraduate ordinary and partial differential equations and/or A104 Vector and Tensor Calculus, or equivalent

Course not offered AY2024-AY2026
A225 Statistical Mechanics, Critical Phenomena and Renormalization Group 2 2 Reiko Toriumi

Classical Mechanics and Quantum Mechanics to advanced undergraduate level.

A226 Synthetic Chemistry for Carbon Nanomaterials 3 2 Akimitsu Narita

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

A227 Quantum Engineering – Simulation and Design 3 2 Jason Twamley

Undergraduate quantum mechanics (full year), especially quantum matrix mechanics for spin, Schrodinger equation (stationary and time dependent), and the operator treatment of the quantum harmonic oscillator.

A228 Quantum Many-body Physics 1 2 Philipp Höhn

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

A229 Statistical Fluctuations and Elements of Physical Kinetics 2 2 Denis Konstantinov

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

A230 Quantum Optics for Qubits 3 2 Hiroki Takahashi

Undergrad-level quantum mechanics and linear algebra

A231 Quantum Information and Communication Theory 2 2 David Elkouss

Linear algebra, probability and statistics. Introductory knowledge of quantum information is helpful, although quantum bits, operations and measurements will be covered here.

A232 Introduction to Quantum Cryptography 2 2 David Elkouss

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.

Alternating years course (from AY2025), alternates with A231 Quantum Information
A233 Stability Analysis of Nonlinear Systems 2 2 Mahesh Bandi

Graduate classical/analytical mechanics
B10 Analytical Mechanics, B13 Fluid Mechanics

Alternate years course, AY2024
A303 Developmental Biology 2 2 Ichiro Masai

Cell biology and/or genetics

A304 Evolutionary Developmental Biology 3 2 Noriyuki Satoh

Cell biology and/or genetics

A306 Neuroethology 1 2 Yoko Yazaki-Sugiyama

Neuroscience background required

A308 Epigenetics 3 2 Hidetoshi Saze

Advanced undergraduate Cell Biology and Genetics

A310 Computational Neuroscience 2 2 Erik De Schutter

Introductory neuroscience, computational methods, programming, mathematics.

A312 Sensory Systems 3 2 Izumi Fukunaga

Background in neuroscience (either at the BSc/MSc level or the OIST basic neuroscience course). Cellular neurophysiology and neuroanatomy.

A313 Cognitive Neurorobotics 2 2 Jun Tani

B46 Introduction to Machine Learning and programming experience in Python, C or C++ are required. Basic calculus of vectors and matrices and differential equations are assumed.

A314 Neurobiology of Learning and Memory I 3 2 Jeff Wickens

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

A315 Quantifying Naturalistic Animal Behavior 3 2 Sam Reiter

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

A316 Neuronal Molecular Signaling 3 2 Marco Terenzio

Basic knowledge of cellular biology and neurobiology.

Passing “Introduction to Neuroscience” or equivalent is required.

A318 Neurobiology of Learning and Memory II 2 2 Kazumasa Tanaka

Basic knowledge of cellular biology and neurobiology. Passing “Introduction to Neuroscience” or equivalent is required.

From AY2024, this course moves to term 2
A319 Microbial Evolution and Cell Biology 1 2 Filip Husnik

Basic understanding of evolutionary and cell biology at the undergraduate level is assumed. e.g., B27 Molecular Biology of the Cell or B23 Molecular Evolution

A320 The Cell Cycle and Human Diseases 2 2 Franz Meitinger

Molecular Biology and Genetics required, e.g.: B27 Molecular Biology of the Cell and B35 Genetics and Modern Genetic Technologies

A321 Macroevolution 2 2 Lauren Sallan

Undergraduate biology, especially evolution. Course B23 Molecular Evolution is required. Contact Prof Sallan if you seek an exemption.

A324 Paleontology and the Diversity of Life 2 2 Lauren Sallan

Basic knowledge of and interest in biology or evolution required, undergraduate biology coursework preferred.

Alternating Years course, from AY2025, alternates with A321 Macroevolution
A409 Electron Microscopy 3 2 Matthias Wolf

Undergraduate mathematics.

B08 Physics for Life Sciences 2 2 Bernd Kuhn
B10 Analytical Mechanics 1 2 Mahesh Bandi

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

B11 Classical Electrodynamics 2 2 Tsumoru Shintake

Undergraduate mechanics and a firm grasp of calculus and vector mathematics

B12 Statistical Physics 1 2 Nic Shannon

Undergraduate calculus and algebra.

B13 Theoretical and Applied Fluid Mechanics 2 2 Pinaki Chakraborty

B10 Analytical Mechanics and/or A104 Vector and Tensor Calculus.

B14 Theoretical and Applied Solid Mechanics 3 2 Gustavo Gioia

B10 Analytical Mechanics and/or A104 Vector and Tensor Calculus.

B20 Introductory Evolutionary Developmental Biology 2 2 Hiroshi Watanabe

No prior knowledge assumed

B21 Biophysics of Cellular Membranes 3 2 Akihiro Kusumi

Biology, chemistry, and/or physics at undergraduate levels

B23 Molecular Evolution 1 2 Tom Bourguignon

Assumes general knowledge in biology

B24 Neuromotor Systems 1 2 Marylka Yoe Uusisaari

This is a basic level course, that will be adjusted accordingly to the interests of enrolled students. No prior knowledge assumed.

B27 Molecular Biology of the Cell 1 2 Keiko Kono

The course is very basic. Non-biology students are welcome.

B29 Linear Algebra 2 2 Liron Speyer

Familiarity with real and complex numbers will be assumed. Ideally, students will have had some previous exposure to mathematical proofs, though this is not strictly required.

Alternate years course, AY2025
B31 Statistical Tests 2 1 Tomoki Fukai

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

B33 Organic Photonics and Electronics 3 2 Ryota Kabe

Undergraduate chemistry

B34 Coral Reef Ecology and Biology 3 2 Timothy Ravasi
B35 Genetics and Modern Genetic Technologies 1 2 Tomomi Kiyomitsu
B36 Introduction to Real Analysis 1 2 Xiaodan Zhou

Undergraduate Calculus or equivalent is required. Multivariable calculus is not a prerequisite. If you are not sure about the prerequisite material, please contact the instructor before enrolling.

Alternate years course, AY2024
B37 Introduction to embodied cognitive science 2 2 Tom Froese

A basis in cognitive science (any discipline) is preferred. Please consult with Prof Froese before enrolling.

Enrollment cap of 9
B38 Human Subjects Research: A Primer 1 2 Gail Tripp

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

B40 Introduction to Polymer Science 1 2 Christine Luscombe
B41 Fundamentals of Ecology 1 2 David Armitage

Undergraduate-level coursework in general biology and calculus are recommended but not required.

B42 The Diversity of Fish 1 2 Vincent Laudet

Curiosity and sense of wonder

B44 Stellar Physics 1 2 Shigehiro Nagataki

Fundamental undergraduate-level physics recommended but not required.

Course not offered AY2024
B46 Introduction to Machine Learning 1 2 Makoto Yamada

No prerequisites. However, without some mathematics and programming background, topics like deep learning are hard to follow.

B48 Introduction to Complexity Science 2 2 Ulf Dieckmann

Basics of calculus, linear algebra, and programming.

B49 Dynamical Systems 2 2 Mahesh Bandi

Classical mechanics, e.g. B10

Alternate years course, AY2023
B50 Introduction to Scientific Computing 1 2 Kenji Doya

Basic skills of computer use.
Familiarity with linear algebra and basic differential equations is assumed, but the course aims to help intuitive understanding of such mathematical concepts by computing and visualization.

NEW for AY2024
B51 An introduction to Quantum Mechanics, Quantum Optics and Quantum Science 1 2 Bill Munro

undergraduate quantum mechanics and linear algebra

NEW for AY2024
B52 Introductory Neuroscience 1 2 Yukiko Goda

Undergraduate biochemistry, biology, and chemistry

NEW for AY2024
B53 Introduction to Applied Cryptography 2 1

No prerequisite within the OIST graduate syllabus. The expectation is that students have a scientific background, with knowledge equivalent to first-year undergraduate mathematics, or more generally, the equivalent to discrete mathematics taught in many science undergraduate degrees.

Five-week intensive course