Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- NTNU - Norwegian University of Science and Technology
- Bangor University
- DAAD
- European Magnetism Association EMA
- Forschungszentrum Jülich
- ICN2
- Karlsruher Institut für Technologie (KIT)
- Leibniz
- Linköping University
- NTNU Norwegian University of Science and Technology
- National Institute for Laser Plasma and Radiation Physics
- Technical University of Denmark
- University of A Coruña
- Università degli Studi di Trieste
- 4 more »
- « less
-
Field
-
magnets, unconventional magnetic systems, and topological materials. The candidate will develop and apply advanced computational techniques, including (TD)DFT and post-DFT analyses, alongside spin dynamics
-
Tasks and responsibilities: The PhD position is framed within the MAIAMI project. The student will work on DFT and molecular dynamics simulations, generating structural and electronic descriptors
-
of radionuclides on clay mineral surfaces using DFT Kinetic Monte Carlo simulations with activation energy barriers as input to simulate large-scale interactions of nuclides with surfaces Preparation and
-
techniques, including (TD)DFT and post-DFT analyses, alongside spin dynamics simulations. The primary goal is to investigate how collective excitations and topological effects influence quantum transport and
-
techniques, including (TD)DFT and post-DFT analyses, alongside spin dynamics simulations. The primary goal is to investigate how collective excitations and topological effects influence quantum transport and
-
comparison with DFT- and MD/MC-based results provided by project collaborators as well as with experimental trends and relevant literature data. Perform high-performance computing (HPC) simulations to analyze
-
at the Humboldt-Universität zu Berlin, where DFT calculations will be performed. running simulations and compare them to experimental results in close cooperation with the experimental group at IKZ. applying
-
, or a related field. Have documented experience in some of the following: Computational materials modelling or quantum mechanical simulations (e.g. DFT, MD). Machine learning / deep learning (preferably
-
interatomic-potentials (MLIPs), refined for molten salt mixtures hosting other nuclear material solutes. We will perform density functional theory (DFT) calculations and molecular dynamics (MD) simulations
-
-to-olefins, syngas-to-olefins) involve the production of hydrocarbons from renewable raw materials. In addition to periodic density functional theory (DFT), ab initio methods and molecular dynamics (MD