40 programming-"https:"-"https:"-"https:"-"https:"-"IDAEA-CSIC" research jobs at Duke University in United States
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support of coastal community resilience. Support for these organizations may include activities such as: conducting research, developing curriculum, designing new programs, recording and analyzing data
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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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. Programming experience in a language such as Python or R. Experience working in a cloud environment such as Microsoft Azure. Experience in writing grant proposals and scientific publications. Strong
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Services, including a clinical ladder program with various steps and opportunities across the health system. Required Qualifications at this Level Education: Graduate of an ARRT or NMTCB-approved program in
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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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Services, including a clinical ladder program with various steps and opportunities across the health system. Required Qualifications at this Level Education: Graduate of an ARRT or NMTCB-approved program in
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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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University Health System is seeking an experienced or new graduate Imaging Technologist to join one of the most comprehensive and advanced CT programs in the region while embracing our mission of Advancing
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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