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Field
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graduate students, and collaborate with clinicians and other collaborators of the lab. MINIMUM QUALIFICATIONS The candidate should have a PhD degree in biomedical/electrical engineering, computer
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computed tomography (CT) reconstruction, including sparse-view and limited-angle algorithms, and the application of advanced machine learning (ML) and computational imaging methods to scientific and
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, distributions, and dynamics in metallic, oxide, and semiconducting systems. This project integrates high-throughput and in situ TEM experimentation with AI/ML-driven image analysis and computational modeling
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electrical engineering, biomedical engineering, computer science, medical physics, neuroscience, or a related field. While this is the preferred background, highly qualified candidates from other scientific
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engineering-based research applicable to cardiovascular disease as part of an extramurally funded project. The successful applicant will create computational models from medical imaging data and run simulations
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experience in optics, computation and electronics. Responsibilities will include designing and implementing optical systems based on quantitative phase imaging with digital holography and electronic systems
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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
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Posting Description POSTDOCTORAL ASSOCIATE, DORKENWALD LAB, McGovern Institute for Brain Research - Dorkenwald laboratory , to develop computational reconstruction, analysis, and modeling
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | about 6 hours ago
science goals to more directly inform requirements and engineering activities. By investing in this extended paradigm early in the design phases, we prioritize science objectives during test selection and
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computational approaches to uncover novel biomarkers and therapeutic strategies for CNS disorders. Key Responsibilities: Develop and implement algorithms for multimodal image fusion, combining data from MRI, PET