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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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and prototype imaging system design Excellent programming skills, Medipix/Timepix detectors, analytical models, forward, and inverse problems, and prototype system development for clinical translation
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R240260 Posting Link https://www.ubjobs.buffalo.edu/postings/54003 Employer Research Foundation Position Type RF Professional Job Type Full-Time Appointment Term Salary Grade E.89 Posting Detail Information
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containment. The prohibitively high computational cost of such simulations necessitates the development of efficient and robust surrogate models for general GCS modeling tasks, especially when inverse modeling
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of linear algebra and numerical optimization Understanding of statistical modeling and inverse problems is desirable Experience with programming languages like Python, MATLAB, or C++ Joy in dealing with
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focus on deep networks for solving inverse problems, learning robust models from few and noisy samples, and DNA data storage. The position is in the area of machine learning, with a focus on deep learning
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: Computational geoscientific skills in using geophysical and geological data for complex geological structure modeling. The research also requires skills in solving geophysical inverse problems. Demonstrated
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the Research Group Nonlinear Optimization and Inverse Problems (Head: Prof. Dr. D. Hömberg) starting as soon as possible. The position is within the Math+ project "Anisotropic microfluids -- fluctuations