56 image-processing-and-machine-learning "UCL" Postdoctoral positions at Yale University
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include: Biomedical sensing and physiological monitoring Edge intelligence and energy-efficient machine learning hardware Radar and wireless signal processing and communications The successful candidate
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. Education and scholarly development The postdoctoral associate will receive structured education in computer vision applications in medical imaging, machine learning, research methodology, responsible conduct
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expertise in in vivo two-photon imaging to study how cortical circuits represent and regulate immune responses. Our group focuses on the “neuroscience of immune responses,” applying circuit-level and systems
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-affiliated with the Yale Stem Cell Center, the Department of Comparative Medicine, and the Department of Surgery, providing a highly collaborative and multidisciplinary ecosystem. The position is ideal
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. Position Overview The successful candidate will develop and apply advanced computational and machine learning methods to large-scale genomic, clinical, and imaging datasets, working across one or more of the
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analysis, kinetic modeling, data analysis, and results dissemination. Qualifications: The ideal candidate will have some prior hands-on experience in preclinical PET/CT or PET/MR imaging, image processing
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Dr Rebecca Dikow - Director of Research Innovation, Yale University Libraries Dr Gary Motz - Head of Computer Systems, Yale Peabody Museum Jeff Campbell – Associate Director for Cultural Heritage
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include: Understand the extent of existing digital images of text, and how the information locked away in them would advance provenance understanding Acquire additional external data, such as the Getty
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skills, including generalized linear models, multiple machine‑learning algorithms, MOFA and multi‑omics pathway analysis. · Strong background in experimental design, quantitative data analysis, and
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spatial omics, longitudinal biomarkers, computer vision, electronic health data) with cutting-edge AI, we aim to fundamentally transform Parkinson’s disease from a disease without cures into a predictable