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frameworks. Course work such as in causal inference or implementation science will be encouraged. Basic Qualifications Applicants should have a PhD or equivalent in epidemiology, economics, public health
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Learning: Experience with PyTorch, TensorFlow, or Hugging Face; embedding models; and model validation/deployment. Causal Inference/Experimentation: Knowledge of experimental design, randomization, and
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or Strategy with expertise in causal inference, econometrics, experimental design, industrial organization, or applied microeconomics. Experience with field experiments, quasi-experimental methods, and
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/deployment. Causal Inference/Experimentation: Knowledge of experimental design, randomization, and causal identification methods. There are no teaching requirements for these open positions. Basic
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and extend skills in developing study protocols, drafting proposals, designing research instruments, creating analytical frameworks. Course work such as in causal inference or implementation science
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frameworks. Course work such as in causal inference or implementation science will be encouraged. Basic Qualifications Applicants should have a PhD or equivalent in epidemiology, economics, public health
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computational research skills in one of the following areas: Economics: PhD in Economics or Strategy with expertise in causal inference, econometrics, experimental design, industrial organization, or applied
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Experience with causal inference Bonus: experience with explainable ML, optimization/decision strategies, or work with EHR/clinical trial data Additional Qualifications: With this appointment, you are