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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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to apply. We seek candidates with expertise in some or all the following areas: density functional theory, deep learning, high-throughput simulations, molecular dynamics, and materials chemistry. Strong
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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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of molecular reactions occurring at the surface of various materials. In addition, computational fluid dynamics (CFD) simulations combined with microkinetic modeling will be carried out to study the heat
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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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analytical tools. Molecular dynamics of semiconductor-oxide interface. Numerical simulations of the oxide condensation process based on force-field data. The topic will require numerical simulations and
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reacting flows. A novel aspect of the project is the use of highly perturbed laminar flame simulations to inform CFD modelling of turbulent combustion in lean hydrogen-air mixtures. Experimental work will be
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. Develop and apply ab initio computations, molecular dynamics simulations, and machine learning models. Collaborate with other researchers within the group and external partners. Present research findings
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algorithms, error correction, or many-body quantum systems. o Proficiency in numerical simulations (e.g., tensor networks, quantum circuit modeling). · For Experimentalists: o PhD in atomic/molecular/optical
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with all institutional training and code of conduct. Ability to work independently based on experience. Knowledge of molecular dynamics simulation and mathematical modeling. Qualifications REQUIRED