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cover letter to be sent to: [email protected] Profil du candidat Diplôme préparé : Bac+5 – Diplôme Ecole d’ingénieurs Compétences scientifiques : atomistic simulations, statistical physics
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. Major duties include: Calculate interaction energies from density-function theory Train machine learning models/potentials Conduct atomistic simulations to explore adsorption/diffusion Analyze
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atomistic behaviour and technical aspects, funded by the Federal Ministry for the Environment, Climate Action, Nature Conservation and Nuclear Safety (BMUKN) (subject to funding approval). The project brings
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Domaine Mathématiques, information scientifique, logiciel Contrat Post-doctorat Intitulé de l'offre Using generative AI to simulate chemically disordered nuclear materials at the atomic level H/F
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adaptive integration methods designed to accelerate atomistic simulations. The approach to be developed will initially integrate spectroscopy data (XPS, SAX, SXRD) to generate candidate structures for S-S
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atomistic resolution. However, many chemically relevant processes involve rare events and activated transitions that occur on timescales inaccessible to conventional molecular dynamics simulations. Overcoming
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and multiscale modelling of helium effects in irradiated Fe–Cr alloys. The position focuses on computational materials science and atomistic simulations. The successful candidate will contribute
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on github . [1] L.M. Hale, Z.T. Trautt, and C.A. Becker (2018), "Evaluating variability with atomistic simulations: the effect of potential and calculation methodology on the modeling of lattice and elastic
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2 PhD Positions in Computational Modelling of Biological Membranes and Adaptive Functional Materials
, you will perform atomistic and coarse-grained molecular dynamics simulations to investigate asymmetric plasma membranes, protein–lipid interactions, membrane domain formation, and the role of sterols
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, interactomics, structural biology, and imaging datasets into predictive computational frameworks. Application of atomistic simulations, coarse-grained modeling, RNA folding prediction, RNA-protein and RNA-small