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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | 14 days ago
black-box prediction; scientific computing (e.g., Python); and peer-reviewed publications. Experience in all areas is not expected; a strong foundation in the underlying physics matters most. Point
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, optimization, or related fields. Proficiency in scientific programming (e.g., Python, Julia, or C++) and experience implementing optimization algorithms. Proven ability to work both independently and in
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and rigorously evaluating new machine-learning methods. • Excellent Python programming skills and strong hands-on experience implementing, training, and evaluating deep-learning models and research
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on imaging concepts, knowledge of Matlab, Python programming languages and commercial software based on the finite element method is a plus, excellent communication skills (written and oral) in English. A very
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modeling and environmental data analysis, such as Python, MATLAB, Fortran, C/C++, or comparable languages and tools. Ability to work with large datasets and to integrate these data with acoustics models
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Engineering, Applied Mathematics, or a related field. Candidates should have expertise in several of the following areas: Scientific software development (C++, Julia, Rust, Python, or similar) Numerical methods
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, collaborate with the top experimentalists, and perform numerical simulations (matlab/python/mathematica). Key Requirements: • Hold a PhD degree in Physics or related fields from a recognized university
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- 4 Additional Information Eligibility criteria - Evolutionary genomics analyses on large NGS datasets -Knowledge on coding (C ,C++, or java), script writing (python, perl), R software and shell Unix
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research on perovskites and/or organic semiconductors Demonstrated experience in global and deconvoluted data fitting, programming in Python and Matlab, as well as electronic structure modeling Intercultural
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, optical instrumentation, programming (MATLAB, Python, or C++), or biomedical imaging. Candidates with strong experimental skills and an interest in translating fundamental engineering advances into clinical