Numerical methods

Develop mathematical models and numerical methods for physical, engineering and complex systems. Research areas include differential equations, scientific computing, optimization, nonlinear dynamics, mathematical physics, network science and multiscale simulation. Faculty teach, supervise students, seek research funding and contribute to curriculum development. English is the working language. Applications received before 1 November 2026 receive full consideration; the search continues until filled.

Develop numerical methods for complex fluid phenomena, including multiphase flows. The research improves unified simulations on Fugaku and prepares their computational performance for FugakuNEXT.

Shiwei Zhang examines how improved numerical methods and cold-atom experiments can jointly resolve difficult problems in quantum matter. The seminar reviews advances in auxiliary-field quantum Monte Carlo and discusses comparisons with experiments. Examples include the crossover between BCS pairing and Bose–Einstein condensation, Hubbard-model physics and possible FFLO pairing in optical lattices.

…describes the alternative tools and numerical methods being developed to interpret forthcoming data.

Classic studies show that in many species – from leech and cricket to primate – responses of neural populations can be quite successfully read out using a measure neural population activity termed the population vector. However, despite its successes, detailed analyses have shown that the standard population vector discards substantial amounts of information contained in the responses of a neural population, and so is unlikely to accurately describe how signal communication between parts of the nervous system. I will describe recent theoretical results showing how to modify the population vect