【导师本人】爱丁堡大学机器学习全奖博士

PhD in Machine Learning @ University of Edinburgh



Fully funded, full-time PhD positions to work in the field of machine learning, with emphasis on deep learning theory, privacy in machine learning, theory of decentralised learning, symmetry in machine learning, and learning theory in economics, with Dr Fengxiang He at the Artificial Intelligence and its Applications Institute, School of Informatics, University of Edinburgh.

Candidate’s profile

• A good Bachelor’s degree (First Class Honours or international equivalent) and/or Master’s degree in a relevant subject (mathematics, statistics, economics, or related subject).
• A strong mathematical background, with an emphasis on analysis, algebra, geometry, differential equation, probability, and statistics. Recipients of mathematics competition medals are highly desirable.
• Proficiency in English (both oral and written).
• Relevant research experiences in machine learning, statistics, etc. are desirable but not necessary.
• Programming skills in Python, PyTorch, TensorFlow, etc. are a plus but not necessary.
  

Contact

Applicants are highly encouraged to contact Dr Fengxiang He (F.He@ed.ac.uk) to discuss your case.

Visiting Scholar/Intern positions are also possible. Please contact Dr He if you are interested.

Environment


The University of Edinburgh is constantly ranked among the world’s top universities and is a highly international environment with several centres of excellence.

The School of Informatics is one of the largest in Europe and currently the top Informatics institute in the UK for research power. The School is exceptionally strong in the area of AI and Theoretical Computer Science, hosting one of the largest groups for AI and Foundations of Computer Science in the world. The successful applicant will be part of the Artificial Intelligence and its Applications Institute and will have the opportunity to interact with the other members of the group and more widely within the School of Informatics.

Supervisor

Dr Fengxiang He is a Lecturer at Artificial Intelligence and its Applications Institute, School of Informatics, University of Edinburgh, and an Affiliate of Edinburgh's Institute for Adaptive and Neural Computation, Edinburgh Future Institute, and Edinburgh Centre for Financial Innovations. He received his BSc in statistics from the University of Science and Technology of China, MPhil and PhD in computer science from the University of Sydney. His research interest is in trustworthy AI, particularly deep learning theory and explainability, theory of decentralised learning, privacy in machine learning, symmetry in machine learning, learning theory in game-theoretical problems, and their applications in economics. He is an Area Chair of ICML, NeurIPS, UAI, AISTATS, and ACML, and an Associate Editor of IEEE Transactions on Technology and Society. Please visit https://fengxianghe.github.io/ for more information.

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