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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 13 hours ago
programming (Python, MATLAB, IDL) with experience in data analysis, visualization, optical raytracing, and simulation software. Ability to develop custom analysis tools. Knowledge of numerical methods
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, etc. - ML-augmented numerical method development. - High-performance computing (HPC). - Quantum algorithm design. - Error correction or error mitigation. City
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physics and magnetic-confinement fusion. Demonstrated research experience in computational physics, numerical simulation, or scientific computing, with a track record of publication in peer-reviewed
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, or related areas. Strong programming and numerical modelling skills using Python, MATLAB/Simulink, Julia, hardware in the loop implementation or comparable tools. Experience with one or more relevant methods
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. Successful candidates will be involved with observational data analysis, numerical modeling of natural hazards, and outreach to local stakeholders. Candidates will present research findings through
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assessment tool that computes SOT efficiencies through autonomous numerical modelling and quantum transport simulations, and COMPASS, an evolutionary optimiser that proposes new candidate heterostructures
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Requirements Applicants must hold a doctoral degree in Mathematics, Statistics, Data Science, Artificial Intelligence or a related field.Basic knowledge of numerical methods for ordinary and partial differential
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local and regional trends. The necessary samples and data have been collected in recent years during expeditions to the area, and include numerous sediment cores, acoustic surveys of the seafloor and sub
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mentoring the next generation of clinician-investigators, having trained numerous students, post-doctoral fellows, and clinical trainees in health sciences research. General Responsibilities As a Researcher
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on research activities already underway in our Materials & Environment section, building up on existing numerical models providing a foundation from which you can build on and contribute your own expertise