Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- DAAD
- Technical University of Munich
- Leibniz
- Nature Careers
- Forschungszentrum Jülich
- Heidelberg University
- University of Göttingen •
- Fraunhofer-Gesellschaft
- University of Tübingen
- Ludwig-Maximilians-Universität München •
- Max Planck Institute for Biogeochemistry, Jena
- Humboldt-Stiftung Foundation
- Hannover Medical School •
- Helmholtz-Zentrum Geesthacht
- University of Bremen •
- Freie Universität Berlin •
- Max Planck Institute for Demographic Research (MPIDR)
- University of Münster •
- ;
- Carl von Ossietzky University of Oldenburg •
- Dresden University of Technology •
- Friedrich Schiller University Jena •
- Helmholtz-Zentrum Dresden-Rossendorf •
- Leibniz Institute for Natural Product Research and Infection Biology - Hans Knöll Institute •
- Leipzig University •
- MPINB
- Max Planck Institute for Biogeochemistry •
- Max Planck Institute for Human Cognitive and Brain Sciences •
- Max Planck Institute for Mathematics •
- Max Planck Institute for Neurobiology of Behavior - caesar, Bonn
- Max Planck Institute for Solid State Research •
- Max Planck Institute for Sustainable Materials •
- Max Planck Institute for the Physics of Complex Systems •
- Max Planck Institute for the Structure and Dynamics of Matter •
- Max Planck Institute of Molecular Plant Physiology •
- Max-Planck-Institut für Kohlenforschung, Mülheim an der Ruhr
- Ulm University •
- University of Bonn •
- University of Cologne •
- University of Passau •
- University of Potsdam •
- University of Regensburg •
- University of Stuttgart •
- University of Tübingen •
- WIAS Berlin
- 35 more »
- « less
-
Field
-
phenomena such as the spread of misinformation or the formation of filter bubbles. For this, we rely on rigorous probabilistic methods to model and analyse the intrinsic complexities of these systems
-
learning and 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 model and analyse the intrinsic complexities of these systems. This research direction requires advancements in modern probabilistic tools, including spatial random graphs, random walks, and Markov chains
-
– depending on the successful candidate’s background and interests. Your tasks: Develop new exact and approximation algorithms and perform complexity analyses for optimization problems on (temporal) graphs
-
“Cellular Plasticity in Myeloid Malignancies: From Mechanisms to Therapies”. In this CRC we will focus on myeloid malignancies as a model to dissect the various molecular mechanisms that enable and regulate
-
xenograft (PDX) models. To this end, the candidate will have direct access to cutting-edge mass spectrometry and advanced bioinformatics infrastructure. The project is part of the collaborative research
-
that define protein structures, functions, dynamics and interactions Protein structure prediction and modelling, e.g. in Rosetta, MODELLER, AlphaFold, etc. Protein-peptide complex prediction or docking
-
civil/electrical/control engineering or mathematics or related study programs with a solid basis in choice modelling and/or reinforcement learning, with knowledge of MATSim is advantageous. Description
-
is funded from 1 November 2025 to 31 October 2028. Who we are: The Independent Research Group Receptor Biochemistry harnesses the complex interplay between proteases and receptors during plant-pathogen
-
“Cellular Plasticity in Myeloid Malignancies: From Mechanisms to Therapies”. In this CRC we will focus on myeloid malignancies as a model to dissect the various molecular mechanisms that enable and regulate