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for the identification, estimation, transportability, and generalization of the causal effects in complex real-world settings. Among others, methodological areas will span: ● Causal inference for spatiotemporal data
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: Sitting using near vision use for reading and computer use for extended periods of time. Lifting (approximately 20 to 30 pounds), bending, and other physical exertion. As part of your application, we
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to estimate the excess number of adverse health events and directly attributable to data centers ● Develop a decision-support platform that allows data center expansion while minimizing environmental exposures
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and at national/international conferences. Collaborate with an interdisciplinary team of biostatisticians, computer scientists, and climate scientists. Contribute to open-source code, reproducible
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with subject matter researchers and investigators in large NIH consortia. Basic Qualifications Ph.D. in a quantitative field, e.g., statistics or biostatistics, computer sciences, computational biology