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Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The Molecular Plasmonics group at the Eindhoven University of Technology has
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Sciences (SLU) performs research and teaching that spans from molecular and cellular mechanisms to the biology and welfare of various animals. Our activities cover a broad spectrum of disciplines, including
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and participating in scientific research (synthesis, analysis, physicochemical characterization of coordination compounds, measurement and analysis of vibrational spectra, preliminary molecular
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on biological processes as well as the impact of biological processes on materials. Our ambition is to foster a dynamic teaching and research environment that is internationally recognised for its excellence in
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molecular dynamics simulations with LAMMPS, and data curation. Scientific context: Our current understanding of polymer viscoelasticity is founded on single-chain models [2]. Such models draw on the fact
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bring expertise in computational methods (such as machine learning, chemo-informatics, molecular dynamics simulation, structural biology) and / or experimental methods (such as biophysical analysis
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Sciences has 45 academic staff and is based at the Kalmar campus. The department is a dynamic environment for knowledge creation and learning, offering education and conducting research in biomedical science
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Molecular Medicine (IKOM)CountryNorwayCityTrondheimPostal Code7491StreetPrinsesse Kristinas gate 3Geofield Contact City Trondheim Website http://www.ntnu.no Street Prinsesse Kristinas gate 3 Postal Code 7491
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microfluidic chip to simulate inter-organ crosstalk and dynamic hormone regulation. A panel of environmentally relevant chemicals and mixtures will be applied to evaluate dose–response effects and mechanisms
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Assistant/Associate Professor - AI-Driven Biomolecular Design, Biotechnology, and Computational Biol
, advanced instrumentation for precise and high-throughput measurements. Computational Biophysics and AI-Driven Drug Discovery – Molecular dynamics simulations, quantum chemistry, and machine learning for drug