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experience with solving large linear systems (e.g. numpy) and large-scale inverse/optimization problems (e.g. scipy, cvxopt, pylops, …). Experience with large data sets and GPU computing (e.g. CUDA); and/or
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techniques for advanced computational imaging systems, combining expertise from Mathematics (Inverse Problems), Computer Science (Efficient Algorithms and High-Performance Computing), and Physics (Image
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involved in analyzing data collected from the TexNet seismological monitoring program and other stations or assets that provide quality data. Comparing different methods and tools for moment tensor inversion
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My interests span a wide range of topics in theoretical physics, including: geometric phases, topological defects in matter and radiation fields, inverse problems (scalar and vector tomography
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deep networks for solving inverse problems, learning robust models from few and noisy samples, and DNA data storage. We are seeking a researcher to join our team in an ERC project on DNA data storage