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17 Mar 2026 Job Information Organisation/Company IMT Atlantique Department Doctoral division Research Field Computer science » Informatics Researcher Profile First Stage Researcher (R1) Positions
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Research Framework Programme? Not funded by a EU programme Reference Number CEX2024-001476-S Is the Job related to staff position within a Research Infrastructure? No Offer Description Prof. Chiara Amorino
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from This Employer https://main.hercjobs.org/jobs/22156632/open-rank-clinical-professor-and-program-director-for-psp-program-in-school-psychology Return to Search Results
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Apr 2026 - 23:59 (Europe/Madrid) Country Spain Type of Contract Permanent Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job
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paradigms (such as self-attention mechanisms) in the context of reduced-order models, as well as their application to areas of interest in engineering like, e.g., computational fluid dynamics, are key
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the job funded through the EU Research Framework Programme? NextGenerationEU Is the Job related to staff position within a Research Infrastructure? No Offer Description Scientific Advisor: João Miguel
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National Aeronautics and Space Administration (NASA) | New York City, New York | United States | 13 minutes ago
. Candidates must possess an exceptional background demonstrating expertise across atmospheric physics, computational modeling, and data science. Knowledge of atmospheric science or meteorology, and computer
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Assistant Director, Treasury Planning (Hybrid) - Financial Services - Treasury Planning & Operations
of investment options. The Group monitors and projects the University’s cash flow, as well as manages all operating lines of credit and a taxable commercial paper program. Debt management includes market analysis
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Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description he project aims to develop a data-driven model to
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, implementation, and analysis of machine learning models for computer vision tasks (40%). Analysis of natural scene statistics in aquatic and terrestrial environments (40%). Design of models to learn texture