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Field
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carry out analyses using vibrational/electronic static and transient spectroscopy • You conduct DFT calculations # Organic synthesis • You synthesize substrates • Based on our
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position within a Research Infrastructure? No Offer Description Activities and context: The fellow will develop machine-learning interatomic potentials (MLPs), trained on density functional theory-DFT data
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will elucidate how silicon disrupts copper wetting and diffusion. A central aspect of this project is the development of a Density Functional Theory (DFT)-accurate machine-learned interatomic potential
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, for DFT activities Where to apply E-mail [email protected] Requirements Research FieldEngineering » Materials engineeringEducation LevelPhD or equivalent Skills/Qualifications The ideal
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Emission Spectroscopy (XES) will be implemented. See http://www.elettra.eu/elettra-beamlines/xafs.html for more information. Job description The successful candidate will join the beamline staff in
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researchers where appropriate. • Contribute to the visibility of the project through publications, presentations and collaborative activities. Where to apply Website https://recruitment.icmab.es/job-list
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of spintronics. Complemented with density functional theory (DFT) calculations to build scientific and technical competence as well as strengthen transferrable skills, this position provides you with the skills
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and validate its accuracy against previous benchmarks for small molecules like PtH. This approach is general and can be directly combined with EOM-CC embedded in point charges, or in periodic DFT
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lifetimes of spins on surfaces. This approach combines electronic states obtained via a periodic quantum embedding (i.e., equation-of-motion coupled-cluster in periodic DFT, pbcEOM-CC) with a coarse-grained
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between faculty, postdoctoral researchers, PhD students, and external partners from academia and industry. The Department of Physics and Astronomy is one of the largest departments at Chalmers University