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Dynamic Atomistic Predictions of Crystalline, Crystal Defect and Liquid Metal Properties NIST only participates in the February and August reviews. Classical interatomic potentials provide a means
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NIST only participates in the February and August reviews. There is a growing need for high-performance materials for various technological applications. To address this need, the NIST-JARVIS (https
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challenging. We seek to address this measurement problem by developing a coherent strategy for integrating inputs from several critical experimental techniques to perform fully atomistic structural refinements
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approach must be combined with mechanistic models that describe the specific microstructure elements. A variety of inputs from both experimental work and simulations (i.e., first principle, atomistic, and/or
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Offer Description Development of atomistic ab-initio simulations and machine learning models for the study of phonon transport, phase transitions, and structural optimization of phase change materials
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and oral Experience with atomistic electronic structure calculations Programming skills Advantages are: Prior knowledge of atomic and molecular physics Thorough and independent working style Knowledge
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theoretical methods and algorithms are required. The research project aims at deriving priors for Bayesian methods from atomistic simulations and machine learning. It also offers the opportunity to work with
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applications for a PhD Student (f/m/d) in the field of Theory and Methods for Non-equilibrium Theory and Atomistic Simulations of Complex Biomolecules Possible projects are variational free energy methods
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processes, multimodal data fusion, physics–ML hybrid modelling (from CFD to atomistic simulations), and AI-assisted hypothesis formulation. MSCA Doctoral Candidate eligibility criteria Applicants must comply
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computational methodologies, ranging from atomistic and electronic-structure–based materials modeling and characterization, via machine-learning and high-throughput methods, to ab initio calculation