Postdoctoral Researcher / Postdoctoral Researcheress

Postdoctoral Researcher in Trustworthy Machine Learning

100%, Zurich, fixed-term

The SML group at the Institute of Machine Learning is looking for highly motivated postdoctoral researchers with expertise in trustworthy machine learning to join our team. The position is available immediately, with an initial appointment for 1 year, renewable up to 3 years.

Job Description

We are seeking candidates with one of the two profiles below, aligned with our lab's main research branches.

• Mathematical Foundations of Trustworthy ML - working on topics such as:
  • (Robust) distributional generalization, transfer learning, causality
  • Multi-objective settings and alignment, RL theory
  • Statistical learning theory, optimization (e.g., implicit bias)
  • Robustness (broadly defined), privacy, memorization, unlearning, interpretability
  • Grounding AI/ML concepts in the social sciences (philosophy, psychology, law)
• Real-World Impact - working on topics including (but not limited to):
  • Real-world problems in scientific or engineering domains using proprietary/real data (beyond public benchmarks), where challenges like distributional generalization, multi-objective trade-offs, causality, privacy, or interpretability are relevant
  • LLM adaptive evaluation and post-training, with clean mathematical proofs for proof-of-concept

Profile

The exact project scope will be tailored to your strengths and expertise. You'll have considerable freedom to pick specific research problems, as long as you collaborate closely with SML team members and help mentor Bachelor's and Master's theses.

We are seeking candidates with the following background:

• Degrees: Bachelor's, Master's, and PhD in Computer Science, Statistics, Mathematics, Electrical Engineering, or a related field
• Solid background:
  1. For the theory profile: theoretical statistics, learning theory, probability theory, and optimization theory.
  2. For the experimental profile: deep knowledge of your application domain, plus sufficient mathematical maturity to write clean proofs.
• Proven research record:
  1. For the theory profile: multiple first-authored publications in ICML, ICLR, NeurIPS, COLT, AISTATS, and similar peer-reviewed venues and/or journals.
  2. For the experimental profile: top journals in your application domain and at least one paper in the ML venues listed above.
• Teamwork: a collaborative mindset and the ability to work effectively in a multidisciplinary team while aligning with our group values.

Workplace

Our lab emphasizes personal growth in core leadership competencies, and we expect you to actively develop along these dimensions.

We Offer

We provide an inspiring, collaborative research environment to support your immersion into an ambitious research agenda. Our team consists of a dynamic and international group of researchers committed to contributing to top-level academic research on trustworthy machine learning. You will have access to state-of-the-art computational resources and a broad network of global collaborators.

Compensation: We offer a competitive salary at the standard rate at ETH Zurich.

Curious? So Are We.

Apply online using the form below. Only applications matching the job profile will be considered.

If you have any questions regarding the position, please contact Prof. Fanny Yang at fan.yang@inf.ethz.ch.