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We are looking for a scholar with research interests in applications of machine learning to health, interested to pursue a Postdoctoral Fellowship at Stanford University, School of Medicine in Palo
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We are inviting applications for a full-time postdoctoral scholar with a strong computational background and interest in leading the development of clinical deep learning and other machine learning
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intelligence/machine learning, psychology, demography, and population sciences. Through cutting-edge research in biobehavioral and social sciences, L.E.A.R.N. aims to spearhead new advances that enhance
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of climate change. The position is geared for a recent PhD graduate with interest in collaborating across disciplines, and expertise in remote sensing, spatial data analysis, machine learning and computer
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for high-dimensional survival data using longitudinal features, and (6) machine learning and deep learning for analyzing time-to-event outcomes, or (7) radiomics and medical imaging analysis.
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machine learning approaches. Experience working with medium to large datasets. Experience analyzing quantitative data, such as kinematics and/or neural/electrophysiological signals. Experience interacting
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the analysis of large and complex population-based datasets, using techniques from natural language processing, machine learning, and deep learning. Dr. Tamang is committed to recruiting and mentoring
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We are seeking a postdoctoral researcher with a focus on developing statistical, machine learning, and causal inferential methods with applications in health care. The postdoc will collaborate
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, genetics, bioinformatics, machine learning, and artificial intelligence, offering varied avenues for mentoring and professional development. Multiple opportunities exist for national collaboration in a
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The highly motivated candidates should be passionate about the development and implementation of machine learning in clinical surgical settings and its implications on healthcare policy