Bayesian optimization, AutoRL, multi-agent RL & AI in the Sciences at National University of Singapore

We are hiring postdoctoral fellows, research assistants, and Ph.D. students interested in advancing the state of the art in learning with less data (AutoML, Bayesian optimization, active learning, physics-inspired AI), with applications to automated reinforcement learning, multi-agent reinforcement learning, advanced manufacturing, and the Sciences for a period of 1 year with possible renewal/extension.

The postdoctoral fellows, research assistants, and Ph.D. students will be based in either the School of Computing of the National University of Singapore (NUS) or CNRS CREATE. The postdoctoral fellows have the opportunity to collaborate with/co-advise the PhD and undergraduate students in our research group.

For more information on our research group, interests, and recent papers in ICML, NeurIPS, ICLR, UAI, AISTATS, and AAAI, visit https://www.comp.nus.edu.sg/~lowkh/research.html.

The postdoctoral fellow and research assistant positions are financially supported by multiple 3- to 4-year research grants involving learning with less data as well as the 5-year DESCARTES project (https://www.cnrsatcreate.cnrs.fr/descartes/) involving hybrid AI.

For the postdoc positions, a successful candidate should have a Ph.D. in computer science, computer engineering, machine learning, statistics, math, data science, operations research or other related disciplines. A good publication record in the premier machine learning and AI conferences and/or journals is preferred. He/she must have a strong proficiency in programming.

For the RA and Ph.D. student positions, a successful candidate should have a Bachelor’s degree in computer science and engineering, statistics, math, data science, operations research or other related disciplines from a reputable university and a strong academic track record (especially in math, statistics, and algorithms courses). A good publication record in the premier machine learning and AI conferences and/or journals is a bonus. He/she must have a strong proficiency in programming.

If you are interested to apply, please send a short cover letter describing your suitability for the position, detailed CV with academic ranking (if any) and publication list, a concise description of research interests and future plans, and academic transcripts to:

Dr. Bryan Low
Email: lowkh@comp.nus.edu.sg
Website: https://www.comp.nus.edu.sg/~lowkh/research.html

We will begin reviewing applications for the positions immediately.