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combine density functional theory (DFT), molecular simulations, and machine-learning force field (ML-FF) development to uncover the factors controlling NHC–surface interactions and to model realistic
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) computational simulations to understand both the electronic states of enzyme intermediates and the transitions between them. As a joint studentship, around half of the project will be based in Manchester and half
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computational condensed matter physics. We seek a motivated researcher with expertise in density functional theory (DFT) to study emergent phenomena in quantum materials. Research Areas - Correlated electronic
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electrocatalysts. Main Tasks and responsibilities: The PhD position is framed within the MAIAMI project. The student will work on DFT and molecular dynamics simulations, generating structural and electronic
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of chemically storing and releasing hydrogen, using methanol as a reservoir. Main activities: • Utilize global optimization codes and perform DFT calculations on supercomputers. • Analyze results and
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UnitedKingdomTime) Position Description: Apply Position Description We invite talented and motivated applicants for PhD and Postdoc positions in the group of Haowei Xu (https://www.haoweixu.com/ ) at the Department
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the Job related to staff position within a Research Infrastructure? No Offer Description Postdoc in Machine Learned Semiconductor Material Properties for Quantum Transport Simulations The simulation
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implement a software engine that automates fault model generation, evaluation, and management. Design and implement advanced test generation methodologies (e.g., test algorithms, Design-for-Test (DfT), Memory
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methods and workflows for chemical problems and experience using simulation software Demonstrated experience with various computational chemistry techniques: DFT-, force-field- and/or molecular-dynamics
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experience with DFT codes will be very highly valued. • Knowledge of chemical reactions and how to model them through computer simulations is highly valued. • Knowledge of classical molecular dynamics