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computational biomedicine. We seek outstanding researchers with training in AI/machine learning, computer science, statistics, mathematics, physics, or related quantitative fields who aim to develop innovative
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will have demonstrated excellence in using modern empirical methods—including econometrics, experimental and quasi-experimental techniques, and/or machine learning approaches for prediction and causal
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with machine learning, natural language processing, or AI methods applied to health data. • Demonstrated expertise in one or more of the following areas: digital health, health AI, health informatics
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function. Our work combines experiments, theory, computational modeling, simulations, machine learning, and evolutionary comparison. We work on yeast, human, and plant transcription factors. We are
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• Experience with additional methods of policy evaluation, e.g., machine learning, text analysis, mixed methods, qualitative research • Experience producing public-facing research summaries for non