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vision for extracting complex patterns, structure, and meaning from images and/or volumes; and (4) new mathematics and algorithms leading to new applications of machine learning and artificial intelligence
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. Analyze complex imaging data using quantitative and computational approaches. Collaborate with a multidisciplinary team of neuroscientists, optical engineers, and data scientists. Present research findings
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/or peer-reviewed journals Required Knowledge, Skills, and Abilities: PhD in Computational Physics, Chemistry, Materials Science, Computer Science/Engineering, Applied Mathematics, or a related field
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: Job Requirements: Required: PhD in computer science, biomedical informatics, electrical engineering, or a related field Demonstrated expertise in machine learning, deep learning, and image-based
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Sign In Create Profile Postdoctoral Research Associate, School of Mining Engineering and Mineral Resources Tucson, AZ, United States | req24974 Apply Now Share Save Job Posted on: 1/28/2026 Back
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, cell biology, molecular biology, bio-computation, or biomedical engineering. Strong oral and written communication skills, organizational capacity, interpersonal, teamwork skills, be highly motivated
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to contribute to cutting-edge research investigating the physiological and psychological impacts of spaceflight. Our program focuses on human analog studies to simulate microgravity and explore
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California Institute of Technology, Physics, Mathematics & Astronomy Division Position ID: Caltech-PMA-PDEXSO [#31534] Position Title: Position Type: Postdoctoral Position Location: Pasadena
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | about 1 month ago
., “Toward ultrafast, ultra-stable imaging arrays: Superlattice doping to enhance the performance of backside-illuminated 3D-hybridized silicon photodetectors,” Journal of Vacuum Science & Technology A 38(2
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will receive full consideration. Key Responsibilities AI-ready data and analysis for the ePIC Barrel Imaging Calorimeter and our Jefferson Lab program Support for the PRad-II and X17 experiments