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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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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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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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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
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Functional Theory (DFT), machine-learned force fields (MLFF), graph neural networks (GNNs), or large language models (LLMs). Extensive Knowledge In: • First-principles atomistic simulations with packages
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in modelling and simulation of nuclear materials using DFT and MD techniques. Specific Requirements Hold a Bachelor's Degree in Physics and a Master's Degree in Physics or Materials Science, or
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and graduate levels (minimum grade of 16 out of 20). Good oral and written English communication skills are required. Experience in computational modeling (DFT and ab initio) with benchmarking
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into polymer matrices. - Use of luminescent species for applications such as sensors. - Knowledge of DFT‑type simulation methods for modeling molecular properties. - Experience writing scientific articles and
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performing DFT/MLIP molecular dynamics simulations; - Analyzing and exploiting results, as well as writing activity reports and scientific publications and presenting results at conferences and working groups
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heat transport at the nanoscale. Couple BTE-based models with information from atomistic simulations DFT of advanced materials and thermal interfaces. Investigate phonon scattering, thermal conductivity