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of XYZs, higher order perturbative calculations inside effective field theories. The particle and nuclear theory group at the TUM School of Natural science is lead by Prof. N. Brambilla and Prof. A. Vairo
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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
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electrolyte and electrodes and their influence on the overall performance and safety of sodium-based batteries and their chemistry You cooperate with partners from theory to optimize charge transport
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Max-Planck-Institut für Kohlenforschung, Mülheim an der Ruhr | M lheim an der Ruhr, Nordrhein Westfalen | Germany | 16 days ago
applications for a position as a PhD student (f/m/d) for in situ structure studies of the activation and adsorption processes of industrially relevant zeolites. Job description The Weidenthaler group is
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Transport Psychology offers, subject to funding, a position as Research Associate / PhD Student (m/f/x) (subject to personal qualification employees are remunerated according to salary group E 13 TV-L
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Description Within the IQST Graduate School framework, the hot atomic vapor spectroscopy group at the 5th Institute of Physics is currently seeking a PhD student. This PhD program is in close
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The DFG-funded Research Training Group (GRK 2717) „Dynamics of Controlled Atomic and Molecular Systems (DynCAM)“ at the University of Freiburg in collaboration with the University of British
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of resources, a position as Research Associate / PhD Student (m/f/x) (subject to personal qualification employees are remunerated according to salary group E 13 TV-L) starting October 1, 2025. The position is
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employers in the region.] The Research Training Group 3082 “Engineering Covalent Bonds in Molecules and Materials (Ec=m2), funded by the DFG (German Research Foundation), will be located in the Departments
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systems on different temporal and spatial scales. For our Research Group Applied Optimization we are looking for a PhD student: New Deep Learning - based Framework for Energy Modelling: Combination