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, primarily for recycling used nuclear fuel to support the deployment of advanced reactors. The selected candidate will develop and optimize novel separations chemistries to recover actinide and rare earth
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complex instruments and run simulations to accelerate discovery. This involves navigating vast parameter spaces, identifying rare or transient phenomena, and dramatically optimizing the use of precious
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computer-aided design software. Collaborative skills, including the ability to work well with other divisions, laboratories, and universities. Ability to demonstrate strong written and oral
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. The successful candidate will have the opportunity to work with interdisciplinary research teams, collaborate with universities, industry, and national laboratory partners, and contribute to the development
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), and cell free methods. Key Responsibilities: Development and optimization of vector constructs and expression condition characterization of protein yields and quality, and large-scale protein production
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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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materials recovery,CO2 electrolysis and fuel cells. Experimental work will involve design, characterization, and degradation studies of model interfaces that can help elucidate their degradation mechanisms
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scientists and engineers are accustomed to. Moreover, the vast majority of the performance associated with these reduced precision formats resides on special hardware units such as tensor cores on NVIDIA GPUs
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(CNM) cleanroom facility, and (2) performing microwave and optical characterization of the heterogeneous devices using Q-NEXT cryogenic capabilities to assess memory performance. A successful candidate
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simulations on the Aurora supercomputer, using AMReX (https://amrex-codes.github.io/amrex/ ) and the lattice Boltzmann method (LBM). The candidate will develop flow/geometry-aware refinement strategies that go