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the umbrella of the public sector innovation initiative at Duke University. Solid background in programming (e.g. Python) is required. The goal is to find a solutions to consider materials infrastructures in
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, United States of America [map ] Subject Areas: Computer Programming Systems Modeling Biochemistry Atmospheric Science Appl Deadline: (posted 2025/02/19, listed until 2025/05/01) Position Description: Apply Position
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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 training
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statistical methods; and experience in analyzing clinical trials data. The applicant must have excellent communication skills (verbal and written), strong programming skills in R with proficiency in UNIX/Linux
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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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experience in analyzing clinical trials data. The applicant must have excellent communication skills (verbal and written), strong programming skills in R with proficiency in UNIX/Linux system. For the meta
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evidence of excellent programming, collaboration, and communication skills. Compensation and Benefits: We offer a very competitive salary and excellent benefits. Visit the Duke University Office of
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, mood disorder models, or equivalent. The candidate should also have proficiency in some surgical neural targeting method. Programming skills and an understanding of mouse genetics are also a plus. The
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of epidemiological methods and study design Strong experience in statistical genetics, omics technologies and their data analysis Proficiency in programming language (e.g., R, Python), statistical software (e.g. SAS
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or scholarship, and 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