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.The tender admission general requirements are those defined in the previous point 6, and additional specific requirements are to have proven experience in (i) molecular dynamics (MD) simulations of condensed
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, Chemistry, Materials Science, or a closely related field. Proficiency in ab initio calculations is required. Prior experience with molecular dynamics simulations is considered an advantage. Candidates will be
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computational biophysics Machine learning and data analysis for biological systems Biomedical imaging and signal processing Molecular modeling and simulations AI applications in bioinformatics or health sciences
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simulation methods, such as molecular dynamics, molecular docking, virtual screenig, and free energy calculations; c) Experience with molecular-based artificial intelligence methods; d) Programming skills. 4
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) points; b) Experience in molecular simulation methods, such as molecular dynamics, molecular docking, virtual screenig, and free energy calculations; c) Experience with molecular-based artificial
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SD- 26053 PHD IN ULTRA-FAST MACHINE-LEARNING INTERATOMIC POTENTIALS FOR NANOINDENTATION OF TIC MA...
dynamics (MD) simulations of different materials families composed of Ti and C. Titanium carbides, for example, exhibit exceptional hardness, high melting point, wear and abrasion resistance, and many other
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molecular dynamics; and enhanced-sampling free-energy methods (e.g., metadynamics and thermodynamic integration) to quantify adsorption and interfacial reaction processes. The research also includes method
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. Job Requirements: PhD degree in Civil and Environmental Engineering or related field Relevant research experience on geotechnical engineering Relevant research experience in molecular dynamics
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experience on geotechnical engineering Relevant research experience in molecular dynamics simulations and computational fluid dynamics will be preferred. Excellent proposal writing and report writing skill
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apply ultra-fast machine-learning interatomic potentials (UFPs, Xie et al., npj Comput. Mater., 2023, 10.1038/s41524-023-01092-7 ) for long, multi-million-atom molecular dynamics (MD) simulations