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platform. The successful candidate will (1) integrate heterogeneous sensors and onboard computing hardware; (2) develop methods for LiDAR-based simultaneous localization and mapping (SLAM), autonomous
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separation and recovery methods for Gallium and Germanium. Major Duties/Responsibilities: Design and synthesize organic ligands, functionalization of resins, polymers. Design and execute adsorption based solid
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passionate about leveraging their experience or developing new expertise in composites manufacturing through a variety of methods from benchtop to pilot-scale. They should then be passionate about leveraging
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quantum magnetism and strongly correlated systems, as well as classical methods such as exact diagonalization, tensor networks or DMRG, and quantum Monte Carlo. Familiarity with inelastic neutron scattering
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column chromatography, recrystallization, and preparative HPLC. Strong expertise in chemical characterization and analytical methods, including NMR, UV-vis, FT-IR, mass spectrometry, HPLC, and related
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or related Applied Economics discipline with a strong quantitative focus. Demonstrable knowledge of applied econometrics and statistical evaluation methods, such as: Difference-in-Differences (DiD
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related to magnetic materials, experience with first-principles electronic structure methods and proven expertise in developing and/or applying advanced AI/ML methods for accelerated materials discovery
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candidate will join the Multiscale Materials (MsM) group within the Advanced Computing Methods for Physical Sciences Section in CSED. The MsM group is dedicated to delivering multiscale, multi-fidelity
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will develop materials and processing technologies that will result in a transformational improvement in gallium and Germanium and rare earth magnetic material extraction methods from naturally occurring
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HPC research within past five years. Preferred Qualifications: The ability to work independently and develop and deploy methods at scale. Experience in high-performance computing and software