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. The ideal candidate will possess not only a deep conceptual understanding of neuroscience but also advanced technical expertise in machine learning, artificial intelligence, and data modeling approaches. We
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in human genetics and population data to experimentally testable mechanisms using powerful genetic models. Projects will combine bioinformatics, genomics, genetics, and systems biology, with
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various computer programs. • A PhD, MD or equivalent with prior relevant training in Immunology, Biology, Physiology, Biochemistry or related field. Required Application Materials: • Summary of previous
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candidate with experience in data analytics, computation, statistical analyses, and decision-analytic modeling who is interested in health policy and economic evaluation. Prior work in any of the following
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testing. Experience with catalyst nucleation, aerosol dynamics, particle formation, or coupled gas-phase and particle-population models. Familiarity with automated experimentation, data acquisition, reactor
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prognostic markers for psychosis in youth at clinical high risk, using state-of-the-art AI models and multimodal neuroimaging, clinical, and cognitive data. The position will emphasize advanced computational
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on physiologic waveform analysis, biomedical signal processing, and computational modeling of continuous clinical monitoring data. The successful candidate will work on projects involving the analysis
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Qualifications: PhD in a relevant field is required; relevant fields include but are not limited to epidemiology, statistics, biostatistics, machine learning, data science, or other quantitative fields. Required
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quantitative modeling using R and/or Python. Experience with PK-modeling within NONMEM, R or Python environments. Strong general computer skills, with the ability to quickly master and implement innovative ML/AI
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interest in this position, your experience and your full CV, including the names and contact info (phone and email) for 3 references. Any additional information regarding how you would attack