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a Research Infrastructure? No Offer Description Join us to pioneer next-generation generative models that accelerate molecular dynamics. We seek a postdoctoral researcher to develop AI surrogates
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internal and external interactions of an organism, i.e. of its dynamics. Yeasts demonstrate a similar variability in resistance in response to oxidative stress, which makes them an ideal model object
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computing algorithm to implement the modelling of inelastic molecular collisions on present-day quantum computing hardware (e.g., IBM-Q, IonQ) within a framework of mixed quantum/classical theory
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deformation behaviors. This will be supported by numerical simulations developed by the LEM where nanoindentation simulations at the atomic scale will be performed by Molecular Dynamic (MD) as well as finite
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, developing molecular models of electrolytes based on polymers, LiFSI salt, and ionic liquids, in contact with active material surfaces. Simulations will be carried out in confined geometries representative
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. In this role, you will help build a systems-level understanding of human biology by developing computational approaches to model the dynamic regulatory programs of cells and tissues. By combining
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is close. Our cohesive campuses make it easy to meet, work together and exchange knowledge, which promotes a dynamic and open culture. The ongoing societal transformation and large green investments in
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the next generation of PV technologies for beyond 2030. The new postdoctoral research position will use materials modelling techniques (DFT, molecular dynamics, machine learning potentials) to investigate
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. Computational chemistry will provide molecular insights into cellulose-solvent interactions and fiber formation. The candidate will develop models at different levels, including molecular dynamics, DFT, and
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. You will develop numerical models for nanoscale heat dissipation to interpret the experimental data. The project will be supervised by Prof. Zijlstra (Molecular Plasmonics group) and co-supervised by