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, listed until 2025/05/19) Position Description: Apply Position Description JOB DESCRIPTION The COOL Lab at Duke seeks a highly motivated postdoctoral researcher to join our group led by PI Dr. Sarah Cooley
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Doctoral Associate Duke Department of Neurosurgery Brain Tumor Omics Program Position Overview We are looking for a dedicated Post-Doctoral Associate to join Dr. Simon Gregory's laboratory in the Brain Tumor
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require self-direction and the ability to work effectively with other team members, undergraduate, graduate, and other post-doctoral researchers in the in lab. Candidates must have obtained their PhD in a
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focus on ion channels, neural circuits, and neuroinflammation. Candidate must have completed the requirements for the PhD degree or equivalent in Neurobiology related fields by the time of beginning the
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) Strong statistical computing skills in R and SAS Excellent writing and communication skills MINIMUM QUALIFICATIONS Education See job description for education requirements. Experience See job description
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, with a focus on innovative statistical methods that boost the efficiency and robustness of clinical trials by incorporating real-world data and taking into account hidden biases. A recent FDA U01 grant
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: A Ph.D. in statistics/biostatistics, computer science, bioinformatics, or other related disciplines is required. Strong interest, research background and experience in the methodology research in
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. Preferred: Experience with in vitro and in vivo electrophysiology, imaging, mouse behavioral assays, and histological analysis. Computational skills are a plus. Why Join the Yang Lab? A proven track record of
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, United States of America [map ] Subject Areas: Computer Science Ecology Environmental Science Climate Science Geography Appl Deadline: (posted 2025/01/27, listed until 2025/04/01) Position Description: Apply Position
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Physical Job Functions Certain positions at Duke University and Duke University Health System may include essential job functions that require specific physical and/or mental abilities. Additional