Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Nature Careers
- Technical University of Munich
- Leibniz
- Forschungszentrum Jülich
- Heidelberg University
- University of Tübingen
- Max Planck Institute for Multidisciplinary Sciences, Göttingen
- DAAD
- Free University of Berlin
- Fritz Haber Institute of the Max Planck Society, Berlin
- Helmholtz-Zentrum Geesthacht
- Max Planck Institute for Biology Tübingen, Tübingen
- Max Planck Institute for Demographic Research (MPIDR)
- Max Planck Institute for Molecular Biomedicine, Münster
- Max Planck Institute for Plasma Physics (Garching), Garching
- Max Planck Institute for the Structure and Dynamics of Matter, Hamburg
- Max Planck Institute of Biochemistry, Martinsried
- Technische Universität München
- University of Greifswald
- WIAS Berlin
- 10 more »
- « less
-
Field
-
department collaborates with numerous national and international partners and with local clinical and research departments. We offer a dynamic, interdisciplinary environment with extensive training
-
and analysis of mathematical methods for novel imaging techniques and foundations of machine learning. Within the project COMFORT (funded by BMFTR) we aim to develop new algorithms for the training
-
institutions, and a research and development provider for numerous companies throughout the world. The INM is a member of the Leibniz Association and has about 250 employees. The INM research group
-
methods to estimate the uncertainty in the daily predictions What do we expect from you? We seek a scientifically curious researcher who is passionate about understanding the environment. You should hold a
-
Student or Postdoc (f/m/x) in the field of Theory and Methods for Non-equilibrium Theory and Atomistic Simulations of Complex Biomolecules Possible projects are variational free energy methods
-
27.06.2025 Application deadline: 15.08.2025 We are seeking an exceptional Postdoctoral Researcher – Evaluation Methods in NeuroAI (m/f/d, E13 TV-L, 100%) to develop statistical methods and
-
further education and training • Systematic start: Structured induction • Healthy at work: Numerous health promotion offers, free membership in UKBfit • Employer benefits: preferential offers
-
theoretical and practical experience with machine learning methods, especially for training of machine learning potentials - development and utilization of ab initio electronic-structure methodology - previous
-
-scale biological datasets derived from both the host and the microbiome, employing advanced statistical methods and cutting-edge artificial intelligence techniques to uncover novel insights
-
ecosystem models. Experience using high-performance computing systems. Proficiency in running numerical ocean models. Familiarity with operating systems such as Linux/Unix and proficiency in shell scripting