Join us

The Kajita Group studies biological phenomena with mathematical models and data analysis. The research itself is described on the Research page. This page is for students considering joining the group: what research you can do, how to join, and what you will learn through research.

Research topics

Undergraduate thesis and master’s projects fall into two broad types. One is to describe biological phenomena with mathematical models and study their mechanisms through simulation and analysis. The other is to analyze publicly available experimental or clinical data and compare them with models. Some projects combine both.

Recent student projects include work on:

• analysis of disease and cell differentiation using gene expression data
• analysis of biomolecular sequence data using machine learning
• mathematical models of pattern formation in tissues and cells
• mathematical models of biochemical reactions and metabolic networks

Even in data-analysis projects, we aim to find the mechanisms of the biological phenomena that generate the data, and principles that hold beyond any particular system. We also make predictions, but we use them as one way to check how well we understand the mechanisms. For this reason we pay close attention to the process by which the data were generated. Data depend not only on the properties of the living system itself, but also on how measurements were made and how the labels used as ground truth were assigned. We analyze data with this process in mind, and ask what can be learned from the results about the biological phenomenon.

Topics are decided through discussion, matching each student’s interests with the research under way in the group.

How to join the laboratory

Undergraduates in the Department of Materials Science and Biotechnology, School of Engineering, can join in the second semester of their third year through the early laboratory assignment system. Graduate students can join through the Applied Chemistry and Biotechnology course of the Industrial Innovation Engineering program, Graduate School of Engineering. Before taking the entrance examination, please contact a faculty member to discuss whether we can accept you. We are also happy to discuss joining as a researcher, for example as a JSPS Research Fellow (PD).

The Bioprocess Engineering Laboratory consists of the Sakurai Group and the Kajita Group. Which group a student works in is decided after assignment, taking into account the student’s wishes and aptitude. For the laboratory as a whole, see the laboratory website.

What you learn through research

In classes, you learn what others have discovered and organized. In research, you find out something not yet known, write it up in a paper or other form, and share it with others. Undergraduate thesis and master’s research are where students learn what this process requires.

Research begins with deciding what question to answer. Starting from a vague interest, you check the literature to see what is known and what is not, and why the answer would matter, and then shape it into a question that data or a model can answer. In undergraduate thesis research, students do this with the supervisor; in master’s research, they do it on their own.

When answering the question, we emphasize checking how far the results can be trusted. For example, we check agreement with analytical solutions in simple cases, and whether known parameters can be recovered from synthetic data, to separate errors in the code from errors in the model. Estimates and predictions are reported with an indication of how large their errors may be. In machine learning, we check that information from the evaluation data has not leaked into training. We then sort out how the results answer the question, what can and cannot be concluded, and what should be asked next.

Research notes record failed attempts as well. Selecting only the conditions that worked, or changing the question after seeing the results, makes chance variation look like an effect. Code and settings are kept too, so that others can reproduce the results by following the same steps.

A paper is read in its author’s absence. Readers cannot ask the author to explain what they do not understand. So students practice writing so that the text alone can be understood and checked: separating claims from evidence, and explaining in a way that makes clear which results would show a claim to be wrong. Citations are checked against the original sources. In seminars, ideas are judged on whether they are correct, regardless of year or position. The supervisor is not always right. If you disagree, make your case with evidence; the supervisor, too, will reconsider when shown evidence.

These ways of thinking and these skills are needed not only in research careers but also whenever engineers make decisions based on evidence and explain them to others. Students also learn the programming needed for data analysis and numerical computation.

The goal of undergraduate thesis research is to read the literature on a question set with the supervisor, answer it with data or a model, check how reliable the answer is, and report it. The goal of master’s research is for students to pose the question themselves and present the conclusion along with its scope and limitations.

How the lab operates

The lab holds a weekly seminar. Depending on the time of year, students either present research articles from English-language journals (journal club) or report on their progress. Twice a year, in August and December, students present their results so far at an interim report meeting.

Knowledge used in research

Research draws on basic knowledge of the life sciences, calculus, differential equations, linear algebra, probability and statistics, and machine learning. Through their research, students learn the ways of thinking in fields such as biophysics, systems biology, mathematical biology, bioinformatics, statistical mechanics, and dynamical systems theory. No programming experience is required. Taking courses in biology, basic mathematics and physics, and programming before joining makes it easier to get started.

Career paths of graduates

Graduates have gone into a wide range of industries, including information and communications, pharmaceuticals, chemicals and materials, manufacturing, food, trading companies, retail, and the public sector. Their occupations are also varied, including research and development, engineering, system development, sales, and planning. Industries and occupations differ between bachelor’s and master’s graduates.

Visits and inquiries

Prospective students are welcome to visit and talk with us. Please contact us via the Contact page.