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ExperienceNone Research FieldTechnologyYears of Research ExperienceNone Additional Information Eligibility criteria PhD in applied physics, optics, biomedical imaging, or a related field; Strong expertise in
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Fellow to join the Tang Lab. The Tang Lab (https://tangxinlab.org/ ) develops interpretable and autonomous artificial intelligence (AI) systems for biological and biomedical research. Our neuroscience
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computational biophysics Machine learning and data analysis for biological systems Biomedical imaging and signal processing Molecular modeling and simulations AI applications in bioinformatics or health sciences
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in Analytical Chemistry is available to work on mass spectrometry research led by Prof. Boone Prentice (https://prentice.chem.ufl.edu/ ) in the Department of Chemistry. We have a position available in
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co-authorship of at least five chapters in monographs in the fields of visual systems, image information engineering, VR/AR technologies or biomedical engineering, experience in applied research and/or
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- Neuroscience & Cell Biol Overview New Jersey’s academic health center, Rutgers Biomedical and Health Sciences (RBHS) takes an integrated approach to educating students, providing clinical care, and conducting
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theranostics and multimodal imaging technologies Neuroinflammation and mechanisms of neurodegeneration AI-driven diagnostic and monitoring solutions integrating biomarkers and sensor technologies in veterinary
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Utilized Physical Demands and Work Environment Overview Statement Posting Details Special Instructions to Applicants Quick Link to Posting https://jobs.rutgers.edu/postings/257430 Campus Rutgers Biomedical
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platform using AI. Involve in the development, implementation of the platform, as well as integration with multi-modal data from electronic health records, medical images, and sensor data from wearable
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Intelligent (AI) systems. We design application-specific image sensors with AI for biomedical and industrial applications. We are looking for new graduate students or postdoctoral fellows to conduct research