We are hiring postdoctoral fellows and research assistants interested in advancing the state of the art in learning with less data (AutoML, Bayesian optimization, meta-learning, active learning), federated/collaborative/multi-party learning (incentive-aware mechanism design, privacy, heterogeneous black-box model fusion), and Bayesian deep learning, with applications to robotics, advanced manufacturing, and precision agriculture for a period of 1 year with possible renewal/extension.

The postdoctoral fellows and research assistants will be based in the School of Computing of the National University of Singapore (NUS) and 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, UAI, AISTATS, and AAAI, you may visit our website.

The postdoctoral fellow and research assistant positions are financially supported by multiple 3- to 4-year research grants involving learning with less data, probabilistic machine learning, and federated learning.

For the postdoc positions, a successful candidate should have a Ph.D. in computer science and 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 position, 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://urldefense.com/v3/__https://www.comp.nus.edu.sg/*lowkh/research.html__;fg!!LIr3w8kk_Xxm!5WVFbxcU0LU-cO7pLLDuS8tAFcDFyyq3ry_tahGU-zowv9dms_ULuK-FZ6N1LUAF2WmIHClC$

<https://urldefense.com/v3/__http://www.comp.nus.edu.sg/*lowkh/research.html__;fg!!LIr3w8kk_Xxm!5WVFbxcU0LU-cO7pLLDuS8tAFcDFyyq3ry_tahGU-zowv9dms_ULuK-FZ6N1LUAF2Rf7E8kA$ >

We will begin reviewing applications for the positions immediately.