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chemistry, electronic structure (static and dynamic aspects), wave function methods (Coupled Cluster, multi-configurational methods, DMRG), Quantum Monte Carlo, DFT-type methods, Green's function methods
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meritorious. Experience with machine learning algorithms and coding for material applications is highly meritorious. Experience in ab-initio and DFT calculations of solid materials, are both meritorious. What
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) with DFT atomistic simulations to investigate the electronic structure and defect states in wide bandgap semiconductor nanomaterials. The goal is to better understand and optimize function
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staff position within a Research Infrastructure? No Offer Description Within the MSCA project: Chiral Nanocluster Materials (CHIRALNANOMAT) https://cordis.europa.eu/project/id/101227458 http
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using machine learning and state-of-the-art DFT and DFPT code-packages. The project will be performed in close collaboration with various research groups in the UK and USA. Research and performing
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– Molecular-Scale Modelling This PhD position focuses on molecular-scale computational modelling of polymer-hybrid anion-exchange membranes. The project involves DFT, molecular dynamics, and Monte Carlo
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. Interpretation of experimental results and integration with theoretical/DFT insights in collaboration with computational partners. Active participation in synchrotron beamtime experiments (XANES, EXAFS) and post
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, or chemical physics. Candidates with expertise in density functional theory (DFT) or theoretical spectroscopy are particularly encouraged to apply. 4 selected references: A. Sasukimar et al
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Healthcare Monitoring We welcome applications from those with expertise in or across these disciplines: Computational materials modeling: DFT, molecular dynamics, phase-field modeling, or multiscale
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of) a PhD in organic chemistry and/or supramolecular chemistry. Experience with supramolecular chemistry, vesicle-based assays, DFT calculations, photophysical characterisation and/or cell biology will be