Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Technical University of Munich
- Nature Careers
- Leibniz
- Forschungszentrum Jülich
- Heidelberg University
- University of Tübingen
- DAAD
- Free University of Berlin
- Fritz Haber Institute of the Max Planck Society, Berlin
- Max Planck Institute for Dynamics and Self-Organization, Göttingen
- Max Planck Institute for Multidisciplinary Sciences, Göttingen
- Max Planck Institute for Plasma Physics (Greifswald), Greifswald
- ; Max Planck Society
- Helmholtz-Zentrum Geesthacht
- Max Planck Institute for Heart and Lung Research, Bad Nauheim
- Max Planck Institute for Astronomy, Heidelberg
- Max Planck Institute for Biology Tübingen, Tübingen
- Max Planck Institute for Demographic Research (MPIDR)
- Max Planck Institute for Extraterrestrial Physics, Garching
- Max Planck Institute for Human Development, Berlin
- Max Planck Institute for Mathematics in the Sciences
- Max Planck Institute for Molecular Biomedicine, Münster
- Max Planck Institute for Nuclear Physics, Heidelberg
- Max Planck Institute for Plasma Physics (Garching), Garching
- Max Planck Institute for the Structure and Dynamics of Matter, Hamburg
- Max Planck Institute for the Study of Crime, Security and Law, Freiburg
- Max Planck Institute of Biochemistry, Martinsried
- Technische Universität München
- University of Duisburg-Essen
- University of Greifswald
- University of Paderborn
- WIAS Berlin
- 22 more »
- « less
-
Field
-
. The candidate will have the opportunity to obtain additional external funding and develop an independent research program during the postdoctoral training. We are looking for an enthusiastic scientist with a
-
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
-
data analysis experts. The main tasks include the analysis of complex biomedical data using modern AI methods, as well as the development of novel machine and deep learning algorithms to understand
-
available in the further tabs (e.g. “Application requirements”). Programme Description The programme enables academics from all over the world to undertake one-to-three-month research residencies
-
bases and instruments in terms of their efficiency and incidence Applied game-theoretic modelling based on 1) and on numerical estimates of the benefits that potential donor countries derive from
-
scientific career. About us TUM’s new Computational Pathology and Medical Machine Learning lab (*2021) develops methods of machine learning (ML) and artificial intelligence (AI) for the analysis of digital
-
: - Quantum computing with qudits, quantum error correction and fault-tolerance - Quantum optics of trapped ions and Rydberg atom arrays - Numerical tensor network techniques - Topological order and (de
-
strategies. We develop new methods with which tumors can be diagnosed more precisely and cancer patients can be treated more successfully. Every contribution counts – whether in research, administration
-
and interest in one of the following fields: • Solid state quantum information science. • Quantum optical properties solid-state systems (e.g. semiconductor quantum dots, colour centers in wice gap
-
human patient samples and cutting-edge AI-driven analyses Validate computational findings through functional laboratory experiments Develop and optimize protocols involving omics methods, immune cell