18 programming-language-"St"-"FEMTO-ST"-"St" Postdoctoral positions at University of California in United States
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oral communication with a record of leading and reporting results. Desired Qualifications: Knowledge of quantum computing algorithms. Familiarity with tensor network methods. Experience programming GPUs
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networks) for simulating quantum computer performance. Relevant publication record and clear, effective written/oral communication of scientific results. Knowledge of quantum information science relevant
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or papers from Ph.D. currently under review Experience with life-cycle costing, life-cycle environmental assessment methods and/or software Strong skills in Python (preferred) and/or a similar programming
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Readiness team as part of NERSC’s Exascale Science Acceleration Program (NESAP ). You will join the team to prepare scientific workflows for NERSC’s next system, the Doudna supercomputer across all program
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practices ● Fluency in programming languages such as R and Python. ● Demonstrated ability to make reproducible code for cleaning, integrating, and modeling spatial/temporal data from multiple sources, spatial
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completed all requirements for a PhD program (or equivalent) except the dissertation in ecology, environmental science, or a closely related discipline at the time of application Additional qualifications
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Lawrence Berkeley National Lab’s (LBNL ) Accelerator Technology & Applied Physics (ATAP ) Division’s Berkeley Accelerator Controls and Instrumentation (BACI) Program has an opening for a
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to provide a full-time training program of advanced academic preparation and research training under the mentorship of a faculty member. Applications are welcome from all areas of theoretical physics, broadly
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to these values. A variety of resources and programs are available to academics, staff, and students that reflect the core values reflected in our strategic plan: “To Boldly Go,” our Principles of Community
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• Demonstrated experience in computational or quantitative research methods. • Strong programming skills in Python. • Experience with high-performance computing, geospatial data, and causal inference methods