Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- DAAD
- Forschungszentrum Jülich
- Nature Careers
- Leibniz
- Technical University of Munich
- Heidelberg University
- Helmholtz-Zentrum Geesthacht
- Karlsruhe Institute of Technology •
- Universität Hamburg •
- ;
- Brandenburg University of Technology Cottbus-Senftenberg •
- Carl von Ossietzky University of Oldenburg •
- Fraunhofer-Gesellschaft
- German Cancer Research Center (DKFZ) Heidelberg •
- Leibniz Institute for Natural Product Research and Infection Biology - Hans Knöll Institute •
- Leipzig University •
- Ludwig-Maximilians-Universität München •
- Max Planck Institute for Infection Biology •
- Max Planck Institute for Molecular Genetics, Berlin
- Max Planck Institute for Sustainable Materials •
- Max Planck Institute of Molecular Plant Physiology •
- Ruhr-Universität Bochum •
- Technical University of Darmstadt •
- University of Cologne •
- University of Göttingen •
- University of Münster •
- University of Regensburg •
- University of Stuttgart •
- University of Tübingen
- University of Tübingen •
- 20 more »
- « less
-
Field
-
science. A wide range of quantum theoretical methods shall be employed. A solid background in quantum mechanics and programming skills are prerequisite for this position, as is the readiness to learn and to
-
Completed university studies (Master/Diploma) in the field of mechanical engineering, physics of related disciplines Enjoy experimental work in international and multidisciplinary teams Communicative
-
theoretical methods shall be employed. A solid background in quantum mechanics and programming skills are prerequisite for this position, as is the readiness to learn and to apply new methods. For an initial
-
part-time, with 65% of the regular weekly working hours (currently 25.35 hours) and should be used for a doctorate. Participation in the accompanying doctoral programme is compulsory. This serves
-
grades in the field of mechanical engineering, material science, physics, computational science or similar, preferably with a specialization in the field of theory and/or simulation Strong understanding
-
harsh process conditions Investigation of the underlying deactivation mechanisms Development of regeneration strategies for deactivated catalysts Coordination with internal and external project partners
-
integrating machine learning and domain-specific knowledge to predict failure arising from hydrogen embrittlement. You will carry out materials testing, computational model development, data processing, and
-
, computational model development, data processing, and code implementation in close cooperation with scientists. The position is limited to 3 years. Equal opportunity is an important part of our personnel policy
-
Leibniz Institute of Plant Biochemistry (IPB) in Halle (Saale), Germany, where we are offering a fully-funded PhD position within the DFG Priority Programme SPP2363: “Molecular Machine Learning”. About the
-
to probe metabolic states and function of control mechanisms. Analysis of strain performance and control mechanisms using computational tools (e.g., flux balance analysis, kinetic models, network component