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encouraged to visit the ESA website: http://www.esa.int Field(s) of activity/research for the traineeship As part of the Wave Interaction and Propagation Section, you will contribute to consolidating
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, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems
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, geophysics, or a related field. The candidate must have a strong background in solid mechanics, inverse problems, and wave propagation. Knowledge of poromechanics is preferred but not required. Also of
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: 2059-2026 URL to this page https://web103.reachmee.com/ext/I003/583/main?site=6&validator=e4575239eb8c0828707e2b716f86c5f8&lang=UK&rmpage=job&rmjob=9994&rmlang=UK
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expertise in several of the following areas: inverse problems, statistics, optimization, uncertainty quantification, and/or computer vision/machine learning. Strong foundation in at least one of: numerical
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5 Jan 2026 Job Information Organisation/Company Czech Geological Survey Department Center for Lithospheric Research Research Field Environmental science » Earth science Researcher Profile First
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21 Feb 2026 Job Information Organisation/Company Université Grenoble Alpes Research Field Technology Researcher Profile Recognised Researcher (R2) Leading Researcher (R4) First Stage Researcher (R1
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Processes, Diffusion models, Flow Matching) and their applications to Bayesian inverse problems, and Literature review around constrained generative modeling or sampling/inference. Usage of GP models as an
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algebra, inverse problems, signal processing, and machine learning. The position requires close collaboration with experts in both image processing and imaging physics, as well as with researchers in
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for this job through MathJobs.Org right now. Please apply at https://jobs.ornl.gov/job-invite/15464/ . Postal Mail: 1 Bethel Valley Road Oak Ridge, TN 37830 Web Page: http://jobs.ornl.gov