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Biostatistics & Bioinformatics Duke University invites applications for a postdoctoral associate in scientific machine learning (SciML) as part of a new NIH-funded Center for Excellence in Multiscale Immune
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Position Summary: The Department of Biostatistics & Bioinformatics (B&B) at the Duke University School of Medicine engages in methodological and collaborative research, providing international and
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responses. Qualifications: A doctoral degree in a relevant field is required, preferably a quantitative field such as epidemiology, bioinformatics, statistics, computer science or engineering. The ideal
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postdoctoral Research Associate (computational biology and bioinformatics area) position is open at Duke University School of Medicine in the lab of Dr. Yi Zhang starting Mar 2026 or later. The ideal candidate
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: • Animal handling experience. • Intellectual curiosity and a growth mindset. • Biostatistics and bioinformatics expertise for scRNA-seq analysis. • Experience with molecular, cellular, biochemical, and
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partnerships with local Duke EM partners. •Strong quantitative skills in the areas of biostatistics, bioinformatics, and/or epidemiology. •Strong programming skills (R or Python preferred). •Knowledge
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, United States of America [map ] Subject Areas: Public Health Biological Sciences Biostatistics Climate Science Health Informatics or Bioinformatics (more...) Environmental Analysis Epidemiology Appl Deadline: (posted 2026
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to support your career goals and provide access to state-of-the-art facilities. Candidates with background knowledge and hands-on experience in transcriptional regulation, 3D-organoids and bioinformatics
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: Post-Doctoral Associate Position Summary: The Department of Biostatistics & Bioinformatics (B&B) at the Duke University School of Medicine engages in methodological and collaborative research, providing
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under Drs Ostrom and Patel’s mentorship. Be You. Requirements: The applicant should have a Ph.D. in computational biology, bioinformatics, computer science, statistics, genetic epidemiology, or a related