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in Python (R and Matlab); • Familiarity with large-scale data processing and cloud computing (Google Earth Engine, BDC, AWS). Application: Send a cover letter (1 page), updated CV, and two references
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ERC funded project on the human gut-brain axis (https://cordis.europa.eu/project/id/865568). The ideal candidate will have strong expertise in data analysis related to gut microbiota and metabolite
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ML models and Python programming. Work Objectives: The main objective of this position is to develop, implement, and validate advanced machine learning methodologies within the scope of the project
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or seabed mining. The candidate will join the Functioning and Vulnerability of Marine Ecosystems group at ICM-CSIC: https://www.icm.csic.es/en/research-group/functioning-and-vulnerability-marine-ecosystems
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 6 hours ago
they are Legal Permanent Residents of the United States. A complete list of Designated Countries can be found at: https://www.nasa.gov/oiir/export-control . Eligibility is currently open to: U.S. Citizens; U.S
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well as time-resolved spectroscopy. Basic programming skills are welcome as the facility is currently implemented with Python. The postdoctoral researcher will work in the Materials and Light Department
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of the CBI which benefits from all the technical means, equipment and technical facilities necessary for the realization of the project. Where to apply Website https://emploi.cnrs.fr/Candidat/Offre/UMR5077
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. Proficiency in Python, MATLAB, or R. Strong quantitative and analytic skills. Preferred Qualifications Experience with evidence-accumulation models (DDM, sequential sampling, Bayesian models). Experience with
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fellow will carry out the development of theoretical and methodological formalisms in relativistic quantum chemistry, as well as their implementation (Python). The position is within the BRUNCH project
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, Python or similar). Familiarity with AI-based or image-analysis research in medicine or ophthalmology. Interest in diabetes-related eye disease, AMD, and/or population-based ophthalmology research. Prior