Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- DAAD
- Forschungszentrum Jülich
- Nature Careers
- Technical University of Munich
- Fraunhofer-Gesellschaft
- Helmholtz-Zentrum Geesthacht
- Leibniz
- Deutsches Elektronen-Synchrotron DESY •
- Dresden University of Technology •
- Max Planck Institute for Solid State Research •
- Max Planck Institute for Sustainable Materials •
- University of Bremen •
- University of Münster •
- 3 more »
- « less
-
Field
-
research spectrum covers a unique range. Institute of Material and Process Design The Institute of Material and Process Design is dedicated to the sustainable and ecological development of innovative
-
combine computer simulations and machine leaning models to extend their compatibility with problems from mechanical engineering and materials research that could not be addressed so far due to their high
-
Your Job: You will work in the Electrocatalytic Interface Engineering department, which is headed by Prof. Dr.-Ing. Simon Thiele. The department focuses on the fabrication, analysis and simulation
-
researcher positions for projects related to photo-electro-mechanical energy harvesting systems, including material synthesis, characterization, device integration, and material simulation. The IGK2495
-
mechanisms occurring in these materials and their synthesis over all relevant length scales (e.g., cutting-edge ab initio methods, atomistic simulation methods, multi-scale modelling, machine learning) High
-
methods/simulations, state-of-the-art computational techniques (e.g. data-driven methods and/or FEM) and/or theoretical material modeling will be given preference We offer: chance to collaborate with
-
Your Job: The electrocatalytic interface engineering department led by Prof. Dr.-Ing. Simon Thiele focuses on synthesis, manufacturing, analysis and simulation of functional materials to find
-
workflows for descriptor based microstructure reconstruction to identify material parameters for crystal plasticity simulations from experimental data through inverse analysis to establish structure–property
-
curate datasets for training ML (e.g. DeepONet) models by materials testing to identify relevant parameters and ensure consistency between simulations and empirical observations dissemination of results by
-
materials testing to identify relevant parameters and ensure consistency between simulations and empirical observations dissemination of results by publications in peer-reviewed journals and presentation