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modeling. Perform predictive modeling using high-performance computing (HPC) infrastructure. Validate computational predictions by collaborating with experimental groups conducting reverse genetics studies
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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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-CCE Scaling Machine Learning. The HEP Division performs cutting-edge research facilitated through advanced detector development, high-performance supercomputing (HPC), and innovative electronic and
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(HPC), and innovative electronic and mechanical engineering. The HEP Intensity Frontier group has recognized roles within the international DUNE collaboration. The successful candidate will be working
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conversion systems (e.g., gas turbine combustors, detonation engines, reciprocating engines, etc.) using CFD solvers (e.g., CONVERGE, Nek5000/NekRS, OpenFOAM, ANSYS Fluent, etc.) on large-scale HPC platforms
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, and optimize for energy efficiency HPC applications and high performance data stream analytics workloads. Use of novel accelerator designs, and automatic methods to model/predict how performance would
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engineering team to translate the models into production. The successful candidate will be part of a cross-lab, highly inter-disciplinary team of experts in ML, applied math, HPC, signal processing
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-house codes and making use of high-performance computing (HPC) tools. Position Requirements Recent or soon-to-be-completed PhD (typically completed within the last 0-5 years) in mechanical, aerospace
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, applied to combustors for aerospace propulsion systems. The work will take advantage of both commercial and in-house codes and leverage high-performance computing (HPC). Perform high-fidelity nozzle-flow
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(H2, NH3). The successful candidate will leverage high-performance computing (HPC) resources at the Laboratory to perform CFD simulations of low-carbon fuel injection, mixing, combustion, and emissions