Postdoctoral Researcher in Machine Learning: The SML group at the Institute of Machine Learning is seeking highly motivated postdoctoral researchers with expertise in trustworthy machine learning. This is an opportunity to contribute to groundbreaking research in a collaborative and inspiring environment located in Zurich.
Postdoctoral Researcher in Trustworthy Machine Learning
Designation
Postdoctoral Researcher
Research Area
Trustworthy Machine Learning
Location
Zurich, ETH Zurich
Eligibility/Qualification
- Degrees: Bachelor’s, Master’s, and PhD in Computer Science, Statistics, Mathematics, Electrical Engineering, or a related field.
- For Theory Profile: Strong background in theoretical statistics, learning theory, probability theory, and optimization theory.
- For Experimental Profile: Deep knowledge of application domains with sufficient mathematical maturity; exposure to learning theory/theoretical statistics.
- Proven research record with multiple first-authored publications in relevant peer-reviewed venues.
Job Description
Candidates will work on one of the two profiles aligned with the lab’s primary research branches:
- Mathematical Foundations of Trustworthy ML
- Topics include robust distributional generalization, transfer learning, causality, and statistical learning theory.
- Real-World Impact
- Focus on real-world problems using proprietary/real data, tackling challenges like distributional generalization and interpretability.
Candidates will have considerable freedom to select specific research problems and are expected to collaborate closely with SML team members, mentoring Bachelor’s and Master’s theses.
How to Apply
Interested candidates should submit the following documents through the online application portal:
- CV
- Two references
- Research statement
- A brief note explaining why you would like to join the group
Applications via email or postal services will not be considered.
For inquiries, contact Prof. Fanny Yang at fan.yang@inf.ethz.ch.
Last Date to Apply
Applications are accepted until the position is filled. Early application is encouraged.
Join us to contribute to top-level academic research in trustworthy machine learning!
