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collaborating experimental research groups. Previous experience in computational modeling of atmospheric aerosols and parallel computing/software development is strongly desired. The term of appointment is based
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Computing Applications group in CSD has an immediate opening for a Postdoctoral Research Associate to design, develop, and deploy machine-learning and high-performance computing workflows, algorithms, and
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learning algorithms for engineering systems Programming experience in FORTRAN, C, or C++ and scripting experience in Python or similar languages Experience with parallel computing environments and Linux
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part of our research program outlined below. Our lab is in the Department of Biochemistry and Molecular Genetics and part of the RNA Bioscience Initiative at the University of Colorado School of Medicine
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. Experience in developing and applying advanced parametric/machine learning postprocessing techniques, producing probabilistic forecasts of hydrometeorological variables, and parallel computing. Proficiency in
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at a fraction of the computational cost. Recently Argonne successfully implemented, AERIS, a state-of-the-art seasonal-to-subseasonal (S2S) weather model AI model. A successful candidate will collaborate
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, Climate Science or a related field. Experience in earth system modeling, data assimilation, and remote sensing of land surface variables. Experience with parallel computing on high performance cluster
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parallel computing. Demonstrated hands-on experience and understanding of developing scientific data management, workflows and resource management problems. Strong problem-solving and communication skills
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chemistry and experience with quantum chemistry packages (e.g., Molpro, NWChem) Strong skills in developing and implementing computational and numerical methods; familiarity with parallel computing on CPU/GPU
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. Integrate the feed chemistry data being developed in a parallel project. Travel to India to help implement the updated model. This would be as needed and no more than two times per year. Conduct a comparative