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. Description: This opportunity is closed to applicants who are Senior Fellows (5-years or more past PhD). The Goddard Earth Observing System (GEOS) global 4D hybrid Ensemble-Variational (EnVar) data assimilation
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. Description: This opportunity is closed to applicants who are Senior Fellows (5-years or more past PhD). Clouds, in particular the frozen phase, bring about the largest challenge and uncertainties
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. Description: This opportunity is closed to applicants who are Senior Fellows (5-years or more past PhD). We are seeking a post-doctoral fellow interested in employing NASA and perhaps non-NASA remote sensing
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. Candidates should not have already been awarded a PhD degree. Website for additional job details https://newton-6g.eu/ Work Location(s) Number of offers available1Company/InstituteIndustrial Systems Institute
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multidisciplinary team specializing in medical imaging and algorithm development. Our work focuses on advancing the use of computer vision, deep learning, and machine learning for analyzing medical imaging modalities
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Researcher (R1) Positions PhD Positions Application Deadline 27 Apr 2026 - 23:59 (Europe/Rome) Country Italy Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework
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24 Feb 2026 Job Information Organisation/Company IMT - Institut Mines-Télécom Research Field Other Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 15 Mar
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6 Mar 2026 Job Information Organisation/Company CNRS Department Laboratoire lorrain de recherche en informatique et ses applications Research Field Computer science Mathematics » Algorithms
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methods that can accurately model such processes remains an open and active research frontier. This PhD project is fundamentally about advancing that frontier, contributing new methods for generative
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candidate will develop and test novel user interfaces that integrate state-of-the-art Large Language Models (LLMs) with novel logic-based multi-robot planning algorithms. This work will be evaluated through