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experimentalists and adapt code for real-world data. Preferred Knowledge, Skills, and Abilities: Familiarity with compressed sensing and/or convex optimization (e.g., total variation minimization). Expertise in
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, biologists, and data scientists. The emphasis will be on enabling high-fidelity image reconstructions from sparse and noisy data, leveraging state-of-the-art methods in compressed sensing, optimization, and
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support. Preferred Knowledge, Skills, and Abilities: Ability to program and debug python code, particularly Jupyter notebooks. Experience in working on collaborative software projects. Environmental, Health
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a related field Experience with radiation transport codes (e.g., FLUKA, Geant4, MCNP etc.) Excellent programming and data analysis skills (e.g., Python, C++, or similar) Solid understanding