86 web-programmer-developer-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" Postdoctoral positions at Argonne in United States
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candidate would be a PhD in geophysical sciences, computer science, or machine learning with experience in developing and verifying deep learning-based models for large dynamical systems (e.g. weather
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modeling of x-ray spectroscopies sensitive to molecular chirality; simulations of x-ray–induced ultrafast electron-transfer, decay, and nuclear dynamics in gas- and liquid-phase systems; and the development
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specifically on developing machine learning-based surrogates and emulators for the dynamics of power grids. This role involves creating advanced probabilistic models that capture the complex behaviors
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, and autonomous materials discovery. This position, supervised by Ashley Bielinski and Alex Martinson focuses on the development of semiconductor materials and the repair of electronic defects
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, machine learning, and control in the energy sector. The postdoc researcher will perform theoretical study and algorithm development on optimization/control/data analytics methods and authorize peer-reviewed
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. The project will involve development of novel parallel algorithms to facilitate in-situ analyses at-scale for multi-million and multi-billion atom simulations. In this role, you can expect to work on enhancing
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to develop innovative technologies to improve the efficiency of resource utilization; to minimize our dependence on imported materials; and to enhance our national security. This position is broadly focused
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multidisciplinary team of scientists and High Performance Computing (HPC) engineers. In the AL/ML group, we work at the forefront of HPC to push scientific boundaries, carrying out research and development in state
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insights and develop reduced order models (ROMs) for boundary layer flows and turbulent combustion. Integrate ROMs with CFD solvers and demonstrate predictive accuracy compared to traditional modeling
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photonic platforms through nano- and meso-scale lithographic fabrication. This position supports two complementary, three-year Laboratory Directed Research and Development (LDRD) projects focused on hybrid