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Postdoc "Interferometric SAR Data Processing and Analysis for Implementation in the 3D-ABC Founda...
Area of research: Scientific / postdoctoral posts Job description: Postdoc "Interferometric SAR Data Processing and Analysis for Implementation in the 3D-ABC Foundation Model" (m/f/d) Background
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21 Feb 2025 Job Information Organisation/Company Université Grenoble Alpes Research Field Geosciences » Geology Researcher Profile Recognised Researcher (R2) Country France Application Deadline 13
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26 Mar 2025 Job Information Organisation/Company Université Grenoble Alpes Research Field Geography » Other Geosciences » Geology Researcher Profile Recognised Researcher (R2) Country France
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, the particle flow incident on the target and particle-matter interactions; - Solving an inverse problem and generating tomographic images, as a function of time, of the target studied; - Participation in on-site
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. Qualifications: You should have (or be close to achieving) a PhD degree. Background within computational methods for inverse problems, ideally tomography. Experience with development of numerical implementations
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Previous Job Job Title Post-Doctoral Associate Next Job Apply for Job Job ID 367852 Location Twin Cities Job Family Academic Full/Part Time Full-Time Regular/Temporary Regular Job Code 9546 Employee
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, Aurora) and one of the brightest synchrotron x-ray sources in the world (APS). Candidates with a background in deep learning, computational physics, computational materials science, inverse problems
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such as PyTorch and TensorFlow. Experience with high-performance computing and/or scientific workflow. Strong background in inverse problems, numerical optimization and image processing. Job Family
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observations; and/or to confront observations with models using self-consistent forward models and/or inverse (retrieval) methods. The ideal candidate will also be a community member in good standing with a
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Postdoc in Machine Learning for Oligopeptide Design (1.0 FTE) (V24.0584) « Back to the overview Job description The advent of modern machine learning (ML) methodology is accelerating scientific