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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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-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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. 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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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
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inside and outside of Yale, including virologists, immunologists, bioinformaticians, computer scientists, and clinicians, (f) presentation in international conferences, and (g) manuscript preparation and
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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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. 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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epidemiologic and statistical methods, including causal inference approaches, machine learning techniques, and high-dimensional data integration methods. Prepare first-authored manuscripts, abstracts, progress
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, comparative genomics, machine learning, and evolutionary analysis to address fundamental questions in molecular biology and human disease. Responsibilities Develop computational pipelines for the discovery
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approaches such as non-coding CRISPR screens, the Massively Parallel Reporter Assay (MPRA), saturation mutagenesis, and synthetic sequence design, alongside machine-learning models of regulatory grammar