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structural models and compute electronic and vibrational properties. Develop and train neural-network or other machine-learned interatomic potentials to enable large-scale molecular dynamics (MD) simulations
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Applications are invited for post-doctoral positions in the Cosmological Physics and Advanced Computing Group (CPAC) Group in Argonne National Laboratory’s High Energy Physics (HEP) Division
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engine modeling code. Perform high-fidelity CFD simulations of turbulent and reacting flows pertaining to gas turbines and detonation engines using spectral element method (SEM). Perform scalability
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contribute to open-source code repositories and documentation. Position Requirements Required skills, knowledge and qualifications: PhD in physical oceanography, coastal engineering, computational science
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for molecular design (e.g., DFT, MD, AI/ML) is desired, but not required. · Strong oral and written communication skills are required. · Ph.D. in an experimental discipline, such as chemistry, materials
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”, “Firstname_Lastname_cover_letter”. Include links to code examples in your CV (e.g., GitHub page, past project repositories). Position Requirements A recent PhD (completed within 5 years, or soon to be completed) in computer science
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developing LLM-based applications using Python APIs. Experience with large scale molecular dynamics (MD) packages e.g. lammps Experience with version control (e.g., Git) and collaborative software development
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and contract. Skill in modeling, processing, and analyzing computational results to inform accompanying experimental efforts. Skill in the use of modern collaborative coding practices. Demonstrated