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Field
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molecular dynamics and path integral simulation methods, machine learning techniques, and electronic structure techniques. Additional background in statistical mechanics and deep eutectic solvents is highly
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. Strong knowledge of heterogeneous catalysis and computational chemistry. Experience with computational modeling (i,e, DFT, and/or molecular dynamics). Familiarity with software such as Material Studio
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Hydrogen is expected to play a key role in the energy and fuel mix of future sustainable transport systems. However, due to its small and light molecular structure, hydrogen exhibits significantly
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graduate students; About the project During our lifetimes, we copy approximately a lightyear’s worth of DNA, and how the different components of the molecular machinery (the replisome) work together to
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of tomorrow and creating novel solutions to major global challenges. Our community is made up of 13 000 students, 400 professors, and more than 4 500 other faculty and staff working on our dynamic campus in
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—from cold interstellar ices to the early stages of planetary systems. The successful candidate will contribute to experimental studies simulating interstellar ice environments under controlled
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, molecular dynamics simulations using ab initio and machine-learning potentials, and the development or application of machine-learning tools for feature extraction, property prediction, and inverse molecular
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thereafter. The project Currently, plant ingredients are often refined to almost molecular purity - and then combined again to create structured foods. This isolation is resource intensive, and the removal
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researchers will work in a dynamic team of staff scientists at Argonne National Laboratory. Within the team we have extensive experience with large scale molecular dynamics simulations, first principles
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/TranSIESTA), or Molecular Dynamics (including hybrid QM/MM or ML-IP simulations) - Apply for computational resources in HPC facilities when needed. - Prepare periodic reports of the results and provide