Postdoc in Machine Learning : Technical University of Munich (TUM) and Helmholtz Munich invite applications for a fully funded Postdoctoral position under the supervision of Dr. Niki Kilbertus. This position is designed for independent researchers eager to set and lead their own research agenda in machine learning for scientific modeling, with opportunities for mentoring, collaborations, and career advancement toward a permanent role in academia.
Summary Table
| Field | Details |
|---|---|
| Title | Postdoc (f/m/x) in Machine Learning for Scientific Modeling |
| Designation | Postdoctoral Researcher |
| Research Area | Machine Learning, Scientific Modeling, Dynamical Systems, Causality, Biomedicine, Climate, Physics |
| Location | Technical University of Munich (TUM) & Helmholtz Munich |
| Salary | German public sector pay (TV-L/TVöD, E14, 100%) |
| Duration | Fixed-term, 1–2 years |
| Leave | 30 days paid leave, flexible working options |
| Start Date | Rolling (apply early) |
| Last Date to Apply | Applications reviewed until position is filled |
Designation
Postdoctoral Researcher (f/m/x)
Research Area
- Machine Learning for Scientific Modeling
- Integration of data-driven and mechanistic approaches for dynamical systems
- Causality and theory-driven ML for science
- Applications in biomedicine, climate science, and physics
Location
- Helmholtz Munich Campus and TUM Garching Campus (dual affiliation)
Eligibility / Qualification
- PhD (or near completion) in a relevant field (e.g., Machine Learning, Computer Science, Physics, Mathematics, or related areas).
- Demonstrated research independence and leadership potential.
- Strong publication record in top-tier ML conferences (e.g., NeurIPS, ICML, ICLR, JMLR) or domain-specific journals.
- Motivation to define research questions, lead projects, and mentor students.
Job Description
The postdoc will:
- Set and drive an independent research agenda in machine learning for scientific modeling.
- Collaborate closely with Dr. Niki Kilbertus, group members, and external partners.
- Publish research in top ML venues and high-impact journals.
- Mentor and co-supervise PhD and MSc students.
- Initiate and manage internal and external collaborations.
- Contribute lightly to group operations and administration.
What We Offer
- Fully funded 1–2 year postdoc position.
- Competitive salary (TV-L/TVöD, E14, 100%).
- 30 days paid leave, flexible working arrangements.
- Access to HPC resources (Helmholtz, LRZ, FZJ).
- Networking opportunities within the Munich AI ecosystem (MCML, MDSI, ELLIS, etc.).
- Generous travel budget for conferences, workshops, and summer schools.
How to Apply
Send a single PDF application in English to:
📧 niki.kilbertus@tum.de
Subject line: “Postdoc Application: [Your Last Name]”
Your application must include:
- Research Proposal (1–2 pages) – Outline research problems you wish to tackle, their significance, and your execution plan.
- Curriculum Vitae with publication list (highlight 2–3 key papers).
- Two references – Letters of recommendation, or names and contact details of referees.
⚠️ Incomplete applications or multiple-file submissions may not be considered.
Last Date for Apply
Applications will be reviewed on a rolling basis until the position is filled. Early submission is strongly recommended.
✅ Equal Opportunity & Accessibility: Applications from all backgrounds are welcome. Preference will be given to candidates with severe disabilities if equally qualified.
