博士申请 | 丹麦哥本哈根大学计算机系招收机器学习方向全奖博士生

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哥本哈根大学

哥本哈根大学（University of Copenhagen）坐落于丹麦王国首都哥本哈根，是丹麦最高学府，4EU＋联盟、国际研究型大学联盟、欧洲研究型大学联盟、欧洲首都大学联盟、欧洲大学协会成员。大学建于1479年，已有500多年历史，从最初只对社会名流开放，现已发展成一所学科全面、集教育与科研于一身的世界研究型大学。

作为欧洲的教育和科研机构之一，哥本哈根大学下属6个学院，包括36个部门以及200多个研究中心，综合排名跻身世界一流。哥本哈根大学位居2021软科世界大学学术排名第30位，2022泰晤士高等教育世界大学排名第96位，2022QS世界大学排名第79位，2022U.S. News世界大学排名第37位。哥本哈根大学科研经费为全欧第4，仅次于剑桥大学、牛津大学和苏黎世联邦理工学院。截至2018年底，共有39位校友曾获得诺贝尔奖。

导师简介

Dr Amartya Sanyal will be starting as Assistant Professor in Machine Learning in the Department of Computer Science in University of Copenhagen from Summer, 2024 and will also be an Affiliated Assistant Professor in the Department of Mathematics. Till then, I am a postdoctoral fellow at the Empirical Inference group in Max Planck Institute for Intelligent Systems, Tubingen where I work closely with Prof. Bernhard Schölkopf. Prior to this, I was a postdoctoral fellow at ETH Zurich AI Center where I worked closely with Prof. Fanny Yang. I completed my DPhil (PhD) at the Department of Computer Science, University of Oxford, funded by the Turing Doctoral Studentship. I was also a member of the Torr Vision Group. My DPhil advisors were Varun Kanade and Philip H.S. Torr. I am also a member of the ELLIS Society. Prior to that, I completed my undergraduate (B.Tech in Computer Science) at the Indian Institute of Technology, Kanpur. On various occassions, I have spent time at Facebook AI Research (FAIR), Twitter Cortex, Laboratory for Computational and Statistical Learning, Montreal Institute of Learning Algorithms, and Amazon ML.

个人主页：

https://amartya18x.github.io/

招生要求和研究方向

I am looking for highly motivated students, with a strong background in probability, statistics, linear algebra, and programming. Reach out to me if you are interested (and refer to this paragraph below in your email) in pursuing a PhD with me on topics in Theory and Foundations of Machine Learning, that you think will also be of interest to me. In your email, please describe your past work, an ideal project you would like to work on in your first year, and why it may be interesting to me.

Some topics I am personally interested in are:

Trustworthy Machine Learning including differential privacy, robustness, certification, fairness etc. and
Learning with limited and imperfect data including unlabelled data, noisy data, and under distribution shift.

See below for specific funded positions starting in 2024. If you already have funding or are interested in co-supervision by me, please reach out to me by email.

项目和岗位

1. Deadline: November, 2023. If you are interested in a fully funded PhD position with me to work on Trustworthy ML with a focus on differential privacy and/or robustness in machine learning, apply on this departmental page. Position starting next August or soon thereafter:

https://employment.ku.dk/phd/?show=160100

2. Deadline: November, 2023. I will be a hiring an ELLIS PhD student starting in September 2024. You can find more details on the ELLIS PhD link:

https://ellis.eu/news/ellis-phd-program-call-for-applications-2023

You will be a part of UCPH Computer Science and we can discuss the choice of the co-supervisor depending on your interests.

3. Deadline: March, 2024. If you are interested in working on the topics mentioned above with me, you can apply to the Danish Data Science Academy (DDSA):

https://ddsa.dk/phdfellowshipprogramme/

联系方式

amsa@di.ku.dk