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contribute? · Contribute to ESRIC’s research on the development of technology for lunar and Martian regolith handling and beneficiation. · Develop and apply modelling and simulation approaches
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The University of Luxembourg invites applications for a fully funded Ph.D. position in machine-learning force fields (MLFFs), uncertainty quantification, and atomistic simulations within the FNR
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), uncertainty quantification, and atomistic simulations within the FNR-funded UMLFF project. MLFFs have transformed atomistic simulations, offering quantum-chemical accuracy for large systems. However, they
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-scale numerical simulation framework to assess mechanical cloaking meta-structures within the ANR–FNR Metacloak project (Robust multi-scale design of meta-structures for mechanical cloaking from additive
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area of machine learning. This includes conducting literature surveys and establishing state-of-the-art; developing necessary experimental and simulation facilities where required; planning, executing