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responsibility is to build and validate these offloading strategies, complete with Python application programming interfaces (APIs), through rigorous simulations and proof-of-concept (PoC) trials. This position is
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data analysis (e.g., surveys, focus groups, experiments, content analysis) Experience or coursework in computational methods and data analysis (e.g., Python, R, NLP techniques). Familiarity with grant
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ExperienceNone Additional Information Eligibility criteria PhD in Earth/environmental sciences/remote sensing with applications in AI Linux, Python, good command of English Additional comments Nothing to mention
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spectroscopy measurement at state-of-the-art large-scale facilities. You will perform quantitative data analysis using programming languages such as Python. You will perform preliminary calculations to interpret
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analytical solutions using tools such as Qlik Sense, Power BI, Python, SQL, and Excel-based analytics tools. Contribute to the design and improvement of data models, data structures, and transformation logic
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National Aeronautics and Space Administration (NASA) | Hampton, Virginia | United States | 10 days ago
programming experience related to finite element analysis and scientific computing in Python. Field of Science: Aeronautics Advisors: George Weber [email protected] (215) 266-7062 Questions about this
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experimental physics, nanofabrication, low temperature measurements, THz optics, Python programming would be an asset. Website for additional job details https://emploi.cnrs.fr/Offres/CDD/UPR2940-ELOBER-173
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, such as Python, MATLAB, or R. • Demonstrated experience in digital twin, EMIS, and data analytics. • Demonstrated experience in database management, dashboard development, and cloud platforms
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or python. An interest in evolutionary biology, comparative genomics or the biology of early-diverging animals would be beneficial, although applicants primarily trained in molecular pharmacology, cell
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such as Python, C++, and MATLAB, scientific computing libraries, geospatial/HDF5 data formats, APIs, containerized environments, automated testing frameworks, and version-controlled collaborative