For Prospective International Students
Students who can be officially affiliated with our lab are:
University of Tsukuba — College of Engineering Systems
University of Tsukuba — Master's Program in Intelligent and Mechanical Interaction Systems (IMIS)
University of Tsukuba — Doctoral Program in Intelligent and Mechanical Interaction Systems (IMIS)
If you are motivated to “make the invisible visible” using mathematical sciences and continuum mechanics, we are open to a wide range of research topics. We welcome students with diverse backgrounds, including those transferring from other universities or academic programs. Supervision will be tailored to each student’s interests and prior training.
Graduate Admissions
To join the lab as a graduate student, you must pass the IMIS entrance examination at the University of Tsukuba. Applicants are required to contact a prospective supervisor in advance. Please reach out to Atsushi Nakao at nakao [at] iit.tsukuba.ac.jp. The admissions process places emphasis on a presentation of your motivation and a research plan, so please consult with us about possible topics beforehand.
Multiple admission windows are offered each year:
July: Recommendation-based admissions
August: General admissions & special selection for working professionals
January–February: General admissions & special selection for working professionals
For details, see the official admissions page (https://www.imis.tsukuba.ac.jp/admission).
Competencies Expected Before Joining
(1) Foundational applied/physical mathematics
Please acquire the fundamentals such as calculus and linear algebra typically covered in the first year of an engineering curriculum. If you are prepared to pass the IMIS Master’s entrance examination, you are well positioned. Basic knowledge of fluid mechanics and inverse problems is desirable but not mandatory; you may learn these after joining the lab (Nakao also studied fluid mechanics and inverse problems as a graduate student at Tokyo Tech).
(2) Foundational programming skills
Our lab primarily uses the following languages:
Fortran — fluid simulations (forward and adjoint)
Python — deep-learning-based fluid simulation and data assimilation
R — multivariate analysis of geophysical data
More important than any specific language is solid programming practice: the ability to design logical flowcharts and solve problems systematically. If you have mastered at least one programming language, that is sufficient. Even with a first language, modern large language models (LLMs) can provide strong support while you learn.