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Doctoral Candidate in AI and Optimization for Machine Learning, Privacy, and Federated Learning University of Zurich in Switzerland
Degree Level
PhD
Field of study
Computer Science
Funding
Funding details are not specified in the announcement. The position is full-time at 80% and fixed-term for a maximum of four years.
Deadline
Dec 1, 2026
Country
Switzerland
University
University of Zurich
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About this position
The University of Zurich's Department of Mathematical Modeling and Machine Learning is inviting applications for an 80% Doctoral Candidate position in AI and Optimization.
The doctoral project will be conducted in the AI and Optimization Lab with Prof. Anastasia Koloskova. Research will focus on theory or the intersection of theory and practice in areas including optimization for machine learning, privacy, machine unlearning, distributed optimization, and federated learning.
Applicants should hold an excellent M.Sc. or equivalent degree in Computer Science, Machine Learning, Applied Mathematics, Electrical Engineering, or a related field. Strong mathematical understanding, programming experience preferably in Python, and prior experience in machine learning, optimization, privacy, or related topics are expected. Fluency in written and spoken English is required.
Applications must include a motivation letter, CV with GPA, school and university score records, and contact details for at least two referees who have agreed to write reference letters. The deadline is 1 December 2026. Employment is expected to start in fall 2027, although spring 2027 or other earlier dates may be possible by agreement. The position is fixed-term for a maximum of four years.
Apply through the University of Zurich online application portal.
Funding details
Funding details are not specified in the announcement. The position is full-time at 80% and fixed-term for a maximum of four years.
What's required
Applicants should have an excellent M.Sc. or equivalent degree in Computer Science, Machine Learning, Applied Mathematics, Electrical Engineering, or a related field; strong mathematical understanding; programming experience, preferably in Python; and prior experience in machine learning, optimization, privacy, or related topics. Candidates should be strongly motivated, interested in innovative research, and fluent in written and spoken English. The application must include a motivation letter, CV with GPA, school and university score records, and contact details for at least two referees who have agreed to provide reference letters.
How to apply
Submit a complete application consisting of a motivation letter, CV including GPA, school and university score records, and contact details for at least two referees through the online application portal. Early applications are encouraged because selection starts immediately.
Make your next move.
Prepare your application
Review drafts and confirm requirements with the university.
Make your next move.
Prepare your application
Review drafts and confirm requirements with the university.