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Experimental Solid Mechanics Laboratory. This position offers a unique opportunity to conduct cutting-edge research at the intersection of materials science, mechanical engineering, and applied physics
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informatics, electrical engineering, or a related field Demonstrated expertise in machine learning, deep learning, and image-based modeling. A strong publication record in top-tier venues (e.g., MICCAI, CVPR
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applicants interested in developing a research program in the field of cancer biology are welcomed to apply. Expertise in the fields of molecular biology, cell biology, and genetics are expected. Experienced
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://sites.rutgers.edu/cahbir/ ) provides a state-of-art facility for brain imaging research and centers the Rutgers-Princeton Center for Computational Cognitive Neuropsychiatry, the Rutgers Brain Health Institute and the
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for this position will be a highly motivated individual with experience in deep learning and medical imaging and a PhD degree in computer science, electrical and computer engineering, biomedical engineering
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, memory, or attention). Work will be performed using a combination of EEG, intracranial recordings (DBS, sEEG), TMS, fMRI, EMG, brain lesions, computational modeling, and other methods. About the Wessel
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normal and pathological feeding and reward processes. Applicant must hold a PhD or equivalent degree in neuroscience, biochemistry, molecular biology, psychology, computer science, biomedical engineering
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/engineering, physics, applied physics, engineering, or a related field completed within the last 5 years. Experience in AI/ML software development for imaging techniques. Proficiency in Python programming
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multiple groups within the X-ray Science Division, the Center for Nanoscale Materials and the Materials Science Division of Argonne. Position Requirements Ph.D. in material science and engineering, physics
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physiology. Demonstrated experience in the development and maintenance of colonies of genetically-engineered mammalian species is required. Demonstrated expertise in advanced surgical approaches in rodents is