PhD in Machine Learning: The Technical University of Munich (TUM) and Helmholtz Munich invite applications for a fully funded PhD position under the supervision of Dr. Niki Kilbertus. The position is focused on developing machine learning methods for scientific modeling, with opportunities to collaborate across multiple research areas, including biomedicine, climate, and physics. The program offers substantial research independence, excellent resources, and access to Munich’s vibrant AI ecosystem.
🎓 Designation
PhD Candidate (f/m/x) – Machine Learning for Scientific Modeling
🔬 Research Area
- Methods-driven Machine Learning for Scientific Modeling
- Integration of data-driven and mechanistic approaches for dynamical systems
- Causality and ML for science
- Potential applications in biomedicine, climate science, and physics
📍 Location
- Technical University of Munich (TUM), Garching Campus
- Helmholtz Munich Campus
- Affiliation with both institutes
✅ Eligibility / Qualification
- Required: Master’s degree (or equivalent, or close to completion) in a relevant field
- Strong interest in research, curiosity, and scientific collaboration
- Skills in rigorous mathematical reasoning and hands-on Python implementation (PyTorch, JAX, HPC environments)
- Strong communication skills in English (written and spoken)
- Commitment to seeing projects through from conception to publication
Encouraged: Applicants from diverse and unconventional backgrounds.
📝 Job Description
As a PhD candidate, you will:
- Conduct independent research in ML for scientific modeling under the guidance of Dr. Niki Kilbertus
- Collaborate with peers and external researchers
- Define your own projects with significant academic freedom
- Publish in leading ML conferences and collaborate on interdisciplinary applications
- Access HPC resources (GPU clusters at Helmholtz, LRZ, FZJ)
- Benefit from structured graduate programs (MCML, MDSI, ELLIS, relAI)
- Receive funding to attend conferences, workshops, and summer schools
🎁 What We Offer
- Fixed-term fully funded PhD (3 years, possible extension to 4 years)
- Salary according to German public sector pay (TV-L/TVöD, E13, 100%)
- 30 days paid leave with high flexibility in work environment
- Generous travel and research budget
- Supportive, diverse, and inclusive research culture
📩 How to Apply
If you plan to start before May 2026:
- Send a single PDF (in English) to niki.kilbertus@tum.de with subject line:
"PhD Application: [Your Last Name]" - Include:
- Research Statement/Proposal (max. 1 page)
- Curriculum Vitae (CV) with projects/publications
- Academic transcripts (Bachelor’s/Master’s certificates)
- Two references (letters or referee contact details)
Applications are reviewed on a rolling basis until filled. Early submission is strongly encouraged.
If you plan to start after May 2026:
Apply through these structured programs and mention Dr. Niki Kilbertus as potential supervisor:
- ELLIS PhD Program (Deadline: October 31, 2025) → ellis.eu
- MCML PhD Program (Call coming soon) → mcml.ai
- relAI Program (Deadline: Likely December 2025) → zuseschoolrelai.de
🗓️ Last Date for Apply
- Rolling basis until filled (for positions starting before May 2026)
- Program deadlines:
- ELLIS → October 31, 2025
- relAI → December 2025 (expected)
- MCML → Announcement pending
✅ Equal Opportunity Statement: Applications are welcome from all backgrounds regardless of gender, culture, ethnicity, nationality, sexual identity, physical ability, religion, or age. Applicants with severe disabilities will be given preference if equally qualified.
