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advanced machine learning and artificial intelligence approaches to analyze data from multi-site cohorts of mothers and infants, with an aim to develop relevant prediction models to improve maternal and
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sensing data in combination with ground truth data to evaluate a range of infectious diseases prevalent throughout the Asia-Pacific. Our lab uses a combination of publicly available data and primary data
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individual to participate in rewarding and cutting-edge research in human motor control and neurophysiology in Parkinson’s disease. This position is primarily geared towards someone with a strong data science
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techniques (SEM and TEM). Experience in cement chemistry and material synthesis will be a plus. Responsibility: Conduct research on laboratory experimentation and analysis of physical and mechanical data
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We have an opportunity in Dr. Vinit Mahajan's lab to perform and direct advanced genetic, genome engineering and stem cell research related to developmental biology and retinal disease. Also
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claims data, electronic health records, and other publicly accessible datasets – all with a keen focus on pediatric pain, sleep, opioids, and perioperative outcomes. Profession-specific co-mentorship will
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and basic mechanistic data to develop immediately usable, predictive tools for clinical testing. Position Description We are currently seeking a highly motivated Postdoctoral Trainee in the field
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the Stanford Center for Biomedical Informatics Research at Stanford University. This position emphasizes conducting real-world evidence studies using various causal inference methods (e.g., target trial
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challenges, particularly for low-income ratepayers. We seek a postdoctoral scholar with electricity system modeling and rate design experience and strong data analysis and management skills. A willingness to
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of both single and multi-band imaging task data, collected over multiple time points, and with a particular interest in mood and cognitive states. The candidate will work on a project funded under an NIMH