Postdoctoral Research Fellow

About this position

Applications are invited for a number of postdoctoral research fellowships in the Department of Physics and the Department of Statistics and Data Science at the National University of Singapore (NUS). Successful candidates will contribute to a Singapore National Research Foundation (NRF)-funded research programme on artificial intelligence for gravitational-wave astronomy, based at NRF's Campus for Research Excellence and Technological Enterprise, and supervised by a team of PIs at NUS: Alvin Chua, Li Cheng, Alexandre Thiery and David Nott.

We seek applicants with strong expertise in scientific analysis for gravitational-wave astronomy and/or statistical machine learning for science. Those with a more general background in applied mathematics, statistics, data science or computational science will also be considered. Relevant areas of expertise can include (but are not limited to) topics such as surrogate modelling, representation learning, self-supervised learning, Bayesian optimisation, Gaussian processes, Monte Carlo methods, reinforcement learning, simulation-based inference, and model misspecification.

The ideal candidates for these positions will possess skills and interests in both theoretical and computational research, a willingness to diversify their expertise and to be involved in cross-disciplinary projects, as well as the disposition to work well independently and as part of a team.

The initial appointment is for one year, with expected renewal up to two or three years in total and could start as early as March 2027. Each position comes with a competitive salary and personal benefits, as well as travel support for international conferences/visits. There will also be opportunities for successful candidates to gain additional experience in supervising research students during their appointment.

Applicants should submit the following materials via e-mail to ai4gw.nus@gmail.com: a cover letter, their CV and list of publications, a short statement of research, and the e-mail addresses of three academic referees who will provide letters of reference. All materials should be received by 15 November 2026 for full consideration.