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, molecular dynamics simulations using ab initio and machine-learning potentials, and the development or application of machine-learning tools for feature extraction, property prediction, and inverse molecular
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to apply. We seek candidates with expertise in some or all the following areas: density functional theory, deep learning, high-throughput simulations, molecular dynamics, and materials chemistry. Strong
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of molecular reactions occurring at the surface of various materials. In addition, computational fluid dynamics (CFD) simulations combined with microkinetic modeling will be carried out to study the heat
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skills while guiding undergraduate and graduate students; About the project During our lifetimes, we copy approximately a lightyear’s worth of DNA, and how the different components of the molecular
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-Integrated 3D Skin Models”, led by Prof. Jonathan Brewer (Department of Biochemistry and Molecular Biology, SDU), Dr. Mike Barnkob and Prof. Torben Barington (Department of Clinical Immunology, Odense
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graduate students; About the project During our lifetimes, we copy approximately a lightyear’s worth of DNA, and how the different components of the molecular machinery (the replisome) work together to
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reacting flows. A novel aspect of the project is the use of highly perturbed laminar flame simulations to inform CFD modelling of turbulent combustion in lean hydrogen-air mixtures. Experimental work will be
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researchers will work in a dynamic team of staff scientists at Argonne National Laboratory. Within the team we have extensive experience with large scale molecular dynamics simulations, first principles
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(ab initio calculations, Molecular dynamics, Computational modeling) and materials science. - Excellent skills and understanding in physical-chemistry of materials. - Excellent verbal and written
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proposals. Grant reporting, managing and monitoring. Work with researchers, and industry partners to gather data and align simulations with practical needs. Identify gaps in existing bio-process models and