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teaching responsibilities. The appointment is generally preparatory for a full time academic or research career. The appointment is not part of a clinical training program, unless research training under
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is generally preparatory for a full time academicor research career. The appointment is not part of a clinical training program, unless research training under the supervision of a senior mentor is the
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should have the ability to and be excited about working in a diverse lab group setting, plan and conduct assessments independently and collaboratively, interpret data, and present results to diverse
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training program, unless research training under the supervision of a senior mentor is a primary purpose of the appointment. The appointee works under the supervision of a scholar or a department at Duke
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, deep learning Computational genomics, network modeling, spatiotemporal/functional data analysis, time-series Strong programming in R and/or Python; best practices in reproducible research Excellent
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and revision Educational Requirements: Work requires a PhD (bio)statistics, econometrics, data science, or related field. Experience/Skills Required: A background in commonly used programming
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is generally preparatory for a full time academicor research career. The appointment is not part of a clinical training program, unless research training under the supervision of a senior mentor is the
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, deep learning, or statistical modeling. Demonstrated experience working with clinical, digital health, or related biomedical data. Proficiency in Python, R, or other scientific programming languages
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may include teaching responsibilities. The appointment is generally preparatory for a full time academic or research career. The appointment is not part of a clinical training program, unless research
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career. The appointment is not part of a clinical training program, unless research training under the supervision of a senior mentor is the primary purpose of the appointment. The Postdoctoral Appointee