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technology. Development of cutting edge foundation models for protein design, small molecule property prediction, or protein function prediction Data generation and curation, including molecular simulation and
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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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/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
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information Ability to model Argonne’s Core Values: Impact, Safety, Respect, Integrity, and Teamwork Desired skills, knowledge and abilities: Experience with large-scale molecular dynamics (MD) simulations
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Postdoc (f/m/d): Machine Learning for Materials Modeling / Completed university studies (PhD) in ...
to collaborative software development and version control systems (Git) # Experience with electronic structure and molecular dynamics simulation codes (VASP, QuantumEspresso, CP2K, LAMMPS) # Motivation to work
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at the APS, integrating x-ray optics and wave propagation models with realistic sample simulations based on dislocation dynamics and molecular dynamics of relevant materials. Significant attention needs
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that requires accurate sub-grid models (e.g., Particle-in-Cell or Vlasov codes) coupled to a hydrodynamic simulation. In general, charged-particle transport is a non-trivial task, not only because of the large
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specializes in fluorescence and Raman-based approaches, integrating advanced microscopic analysis to gain molecular-level insights into complex materials and systems. The lab is internationally recognized
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CFD methods DFT and Molecular modelling linked to CCUS Strong analytical and problem-solving skills, with an ability to interpret and analyze simulation and/or experimental results. Ability to work in
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photo-bases. The work will focus on modeling of adiabatic and nonadiabatic photochemical processes to capture excited states dynamics using an array of ab initio molecular dynamics methods for excited