44 programming-language-"Data-driven-Materials-Modeling" Postdoctoral positions at Duke University
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. Duties and Responsibilities : Design and perform experiments related to funded programs, specifically: synthesize, characterize and evaluate candidate compounds in microbiological assays; collect and
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on implementation science approaches, to guide implementation, evaluation, and continuous learning. Lead and conduct analyses that generate actionable insights for policy, program improvement, implementation, and
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multidisciplinary translational neuro-oncology research program focused on immunotherapy, biomarker discovery, and spatial biology. In this role, you will help advance innovative research embedded within investigator
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processing with knowledge of quantum theory / information science. SKILLS: Proficiency in English language including writing and oral communication. Duke University is an Equal Opportunity Employer committed
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independence in a highly collaborative environment that values mentorship, innovation, and professional growth. Be Bold. Join a research program focused on understanding how tumors evolve during and after
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Bayesian inference, likelihood-free inference, uncertainty quantification, identifiability analysis, or scientific machine learning. Strong programming skills (Python, Julia, Matlab, C++, or similar). Strong
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programs with employer contributions, tuition assistance for employees and their children, and more. Anticipated Pay Range: Duke University provides an annual base salary range for this position based
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database to support clinical and translational epilepsy research initiatives. Design, develop, and execute an independent research project exploring the relationship between sleep and epilepsy. Plan and
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records of research activity, which remains the property of Duke University upon termination. Monitor progress of research projects and coordinate with Principal Investigator and Program team to stay
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programming skills in R. Proficiency working within UNIX/Linux environments. Preferred Qualifications Experience with Bayesian statistical methods. Experience with hierarchical modeling and mixed effects models