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博士申请 | 新加坡国立大学刘谦雄老师招收机器学习方向全奖博士/博后/RA

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2024-08-23

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新加坡国立大学

新加坡国立大学(National University of Singapore),简称国大(NUS),是亚洲顶尖、国际知名的研究型大学(2022年排名在泰晤士高等教育世界大学排名中世界排名第21位,QS世界大学排名中排名第11位)。其电子计算机工程系(ECE)排名世界第14位(2021ARWU)。


导师简介

Dr. Bryan Low is an Associate Professor of Computer Science at the National University of Singapore and the Director of AI Research at AI Singapore. He obtained the B.Sc. (Hons.) and M.Sc. degrees in Computer Science from National University of Singapore, Singapore, in 2001 and 2002, respectively, and the Ph.D. degree in Electrical and Computer Engineering from Carnegie Mellon University, Pittsburgh, Pennsylvania, in 2009. His research interests include probabilistic & automated machine learning, planning under uncertainty, and multi-agent/robot systems.

Dr. Low is the recipient of the (1) Andrew P. Sage Best Transactions Paper Award for the best paper published in all 3 of the IEEE Transactions on Systems, Man, and Cybernetics - Parts A, B, and C in 2006; (2) National University of Singapore Overseas Graduate Scholarship for Ph.D. studies in Carnegie Mellon University (CMU) in 2004-2009; (3) Singapore Computer Society Prize for Best M.Sc. Thesis in School of Computing, National University of Singapore in 2003; and (4) Faculty Teaching Excellence Award in School of Computing, National University of Singapore in 2017-2018.Dr. Low has served as a World Economic Forum’s Global Future Councils Fellow for the Council on the Future of Artificial Intelligence and Robotics from Sep 2016 to Jun 2018 and an IEEE Robotics & Automation Society (RAS) Distinguished Lecturer for the IEEE RAS Technical Committee on Multi-Robot Systems in Mar 2019. He has served as an organizing chair for the IEEE RAS Summer School on Multi-Robot Systems in Jun 2016, the AI Summer Schools in Jul 2019 and Aug 2020, and the NeurIPS 2021 Workshop on New Frontiers in Federated Learning. Dr. Low has also served as associate editors, area chairs and program committee members, and reviewers for premier AI (specifically, multiagent systems, AI planning, robotics, machine learning) conferences: IJCAI, AAAI, ECAI, AAMAS, ICAPS, RSS, IROS, ICRA, CoRL, NeurIPS, ICML, AISTATS, ICLR and journals: TKDE, JMLR, JAIR, MLJ, TNNLS, T-ASE, IJRR, T-RO, AURO, JFR, TOSN, JAAMAS. He was the top 5% reviewer for ICML 2019, top 33% reviewer for ICML 2020, and an expert reviewer for ICML 2021.

招生信息

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

A recorded seminar on our recent works is available here:

https://www.youtube.com/watch?v=MU6HCFm65aE

招生要求

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.

申请方式

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 (lowkh@comp.nus.edu.sg)

We will begin reviewing applications for the positions immediately.







实习内推

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非凸科技北京智源人工智能研究院小红书社区技术部TikTok推荐算法团队视见睿来Mobileye阿里CCO智能服务算法团队中移动金融科技有限公司格灵深瞳合肥研发中心智源人工智能研究院小红书社区技术部阿里巴巴淘系搜索算法团队百度搜索策略部相关性团队粤港澳大湾区数字经济研究院中科院香港AI与Robotics创新中心智源人工智能研究院阿里巴巴CRO线西湖大学学习与推理系统实验室百度商业研发部模型团队阿里达摩院决策智能实验室同花顺问财团队华为云算法创新Lab智源人工智能研究院淘系搜索算法技术团队秘塔科技美柚研究院百度商业研发部之江实验室蓝箭航天华为诺亚方舟实验室腾讯微信事业群快手商业化算法团队阿里妈妈智能广告平台团队群核前沿技术研究院京东零售内容算法部

高校招生

香港中文大学(深圳)吴保元教授香港大学赵恒爽老师佛罗里达大学陈世刚教授东北大学徐啸林老师香港理工大学AIMS课题组新加坡国立大学Robby T. Tan教授香港大学刘希慧老师香港科技大学陈浩老师新加坡国立大学尤洋老师香港浸会大学徐建良教授新加坡iTrust研究中心香港大学蒋海波教授佛罗里达州立大学刘毅老师香港中文大学(深圳)纪冬旭老师香港科技大学(广州)梁宇轩老师北京信息科学与技术国家研究中心香港中文大学(深圳)何继善院士香港中文大学(深圳)林天麟老师休斯顿大学林森老师中国科学院深圳先进技术研究院南加州大学黄强教授埃因霍芬理工大学武垚欣老师香港科技大学(广州)白云老师香港理工大学林婉瑜老师上海交通大学张希教授亚利桑那州立大学阿联酋MBZUAI宫明明教授香港科技大学(广州)骆昱宇老师香港理工大学Lap-pui Chau教授香港浸会大学北京大学分子影像/医学智能实验室大湾区大学杨斯崑教授香港理工大学智慧航空优化研究团队新加坡国⽴⼤学Gim Hee Lee⽼师香港科技大学屈华民教授清华大学机器学习课题组凯斯西储大学印宇老师香港理工大学智能计算实验室澳大利亚国立大学孙萧育老师香港中文大学(深圳)数据科学学院新加坡国立大学刘钿渤老师西湖大学吴泰霖老师香港理工大学李青教授


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