General Information / How to apply
- I have multiple open positions for Ph.D. students, postdocs, master theses, interns, and other collaborations on
- optimization
- theory of machine learning
- federated learning
- fairness, security, privacy, robustness
- Requirements
- A bachelor/master degree in Computer Science, Mathematics, Statistics (or related fields)
- Excellent English (knowledge of German is not required)
- Strong background in either (or multiple): machine learning/optimization/programming
- What we offer
- Full-time work contract (see also this blog post about life as a PhD student in Germany by a CISPA colleague).
- Excellent research environment
- Strong supervision
- World-class collaborations
- Please send me and email with your CV, mentioning the position you apply for, a research statement and motivation.
- If you apply for a [PhD], a [Postdoc], a [HiWi], or [Intern] position, please fill our the corrsponding form.
- Applications will be reviewed on a rolling basis (I might not respond to generic requests).
HiWi and Internships
- If you are a student at UdS (or elsewhere in Germany) prior to completion of your masters, you can apply for (paid) reserach work (up to 19hrs a week). Please use this form: [HiWi].
- If you are a student you can apply for an internship (see also the Young Researcher Internship Program). Please use this form to contact me directly: [Intern].
- Please note that internships are paid, but we cannot provide travel funding to travel to Germany (by German law).
- If you need a visa, please apply at least 6 months prior to the desired starting date.
- [Winter 22/23]: I have at least 3 openings for projects related to (i) Federated Optimization, (ii) Asynchronous Methods and (iii) Decentralized Optimization.
Highlighted Positions
- Fully funded 4-year PhD (application deadline December 15, 2023)
Possible research topics during your PhD include theory and algorithms for- federated (or decentralized) learning
- collaborative learning
- deep learning optimization
- privacy preserving machine learning
- fairness, robustness, personalization
Requirements: The candidate is expected to have an excellent degree at the MSc level in mathematics, statistics, computer science or a related discipline. A solid mathematical foundation (e.g. probability theory, statistics, calculus, and linear algebra) is a must, experience in optimization, machine learning, data science or with a ML framework such as e.g. PyTorch, is a plus.
- internatioal project - 2-year postdoc in optimization for (distributed) deep learning
Together with Dr. Tao Lin (TT Faculty at Westlake University, P.R.China) I am looking for a postdoc. The candidate will be affiliated with Westlake University (two-year contract) and will interact and collaborate closely with both faculty in a hybrid collaboration form, with the possibility to visit each group with a similar time percentage. He/she will work on foundational machine learning challenges and will lead projects. We offer a competitive salary. Please reach out to us if you have further questions on the project organization.Applicants with a Ph.D. degree and a strong academic track record in one or more of the following research topics are encouraged to apply: (a) optimization for deep learning, (b) distributed and federated optimization, (c) efficient/robust deep learning and inference.
- Opt4Bio
The group of Sebastian Stich is looking for a PhD candidate with a strong research interest in the analysis and development of optimization strategies for training machine learning models. It will be a plus if the student is motivated to work on theoretical challenges that arise in practical application in the fields of biology and health (e.g., structured, or multimodal data, low sample sizes, etc.). Within this project, the student will have the opportunity to collaborate with partners within the Helmholtz AI unit.Requirements: The candidate is expected to have an excellent degree at the MSc level in mathematics, statistics, computer science or a related discipline. A solid mathematical foundation (e.g. probability theory, statistics, calculus, and linear algebra) is a must, experience in optimization, machine learning, data science or with a ML framework such as e.g. PyTorch, is a plus.
Highlighted Student Projects
- TBA