We are hiring postdoctoral fellows and research assistants interested in advancing the state of the art in collaborative/federated/multi-party learning (incentive-aware mechanism design, data valuation, privacy, heterogeneous black-box model fusion) and machine unlearning, with application to trusted data/model sharing 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, visit https://www.comp.nus.edu.sg/~lowkh/research.html). In particular, see the tab on "Trusted Model/Data Sharing and Data Valuation". A recorded seminar on our recent works is also available here: http://youtu.be/IhizVZdUv6k The postdoctoral fellow, research assistant, and Ph.D. student positions are financially supported by a 4-year AI Singapore research grant award titled "Toward Trustable Model-centric Sharing for Collaborative Machine Learning" (https://ids.nus.edu.sg/TrustedCollabML.html). 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 and See-Kiong Ng Emails: lo...@comp.nus.edu.sg <https://groups.google.com/u/3/>, n...@comp.nus.edu.sg <https://groups.google.com/u/3/> Websites: https://www.comp.nus.edu.sg/~lowkh/research.html, https://ids.nus.edu.sg/TrustedCollabML.html We will begin reviewing applications for the positions immediately. -- Regards, Bryan Low Associate Professor of Computer Science, National University of Singapore Director of AI Research, AI Singapore
_______________________________________________ uai mailing list uai@engr.orst.edu https://it.engineering.oregonstate.edu/mailman/listinfo/uai
