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experimental studies, mechanistic modelling, time-resolved data analysis, and machine learning to develop and validate predictive models linking process signals to reaction behaviour, progressing from controlled
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computational models and machine learning methods, as well as experience in repertoire data analysis. Website for additional job details https://emploi.cnrs.fr/Offres/CDD/UMR8023-CLAMAR-001/Default.aspx Work
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following areas is desirable: collection and analysis of dense nodal seismic datasets, ambient noise tomography, high-performance computing, machine learning applications in observational seismology, and
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-Chem • You will be contributing to the development of machine learning models used on data from Poleno Jupiters, applying Python and machine learning. • The position will focus on implementing
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analysis. Excellent programming skills in Python and experience with deep-learning frameworks (preferably PyTorch). Experience developing, training, validating, and optimising machine-learning models
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will contribute to and lead research in the following areas related to our current and past projects https://gxrlab.rf.gd/research/ : Intelligent Motor Skill Learning: Developing AI-driven, physics
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | 5 days ago
-series. Experience exploring machine learning and deep learning techniques for geospatial applications is highly desirable to effectively engage with Earth observation foundation models. Technical
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world and a suite of associated machine learning tools. The incumbent will be advised by Dr. Laurel Symes (CAPS, [email protected]). Depending on the research direction, collaboration and additional
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atomistic simulations, scientific machine learning, reaction modeling, and integration of computational and experimental data. The associate will develop reproducible computational workflows, collaborate with
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técnicas de machine learning e IA. Sólidos conocimientos en análisis y tratamiento de datos, programación y desarrollo de modelos analíticos. Experiencia con bases de datos y herramientas de análisis