Job description
As a successful candidate, you will work on the development of machine learning methods in the AI for Materials Science (AiMat) group of Prof. Dr. Pascal Friederich.
Your responsibilities will include:
1. Development of machine learning methods in collaboration with partners of the DFG Excellence Cluster “3D Matter Made to Order,” with a focus on ML potentials for complex atomistic simulations of laser 3D printing processes
2. Research in the areas of accelerated atomistic simulations, universal ML potentials, and model distillation
3. Collaboration with experimental partners in the 3DMM2O project to apply and validate the developed ML potentials
4. Preparation of scientific manuscripts and presentation of research results at workshops and conferences
In addition to scientific work, there is the opportunity of pursuing a PhD.
Starting date
01.02.2026
Personal qualification
5. A Master’s degree in Computer Science or a Natural Science from an internationally recognized academic institution
6. Theoretical and practical experience in the fields of machine learning and deep learning Experience in applying machine learning methods in an interdisciplinary context is an advantage
7. Experience in the field of machine-learned potentials and/or molecular dynamics simulations and/or density functional theory is an advantage
8. Experience in developing and training large models or performing simulations on high-performance computing systems is desirable
9. Ideally, practical research experience as well as experience with publications in relevant scientific fields
10. Experience in programming with Python, especially with libraries such as PyTorch
11. Fluent English skills
12. Strong communication and presentation skills