2,753 data-"https:" "https:" "https:" "https:" "https:" "https:" "SciLifeLab" "IFM" "IFM" positions at Duke University in United States
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, sound judgment, ability to operate in a de-centralized, nuanced environment, and experience handling confidential information. Willingness to travel extensively and work evenings/weekends. Anticipated Pay
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mentorships with clinical pharmacists, give professional presentations, and conduct research and quality improvement projects. For more information, see https://regionalpharmacy.duke.edu/internship/ Work
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/or Data-Driven Design Product and Hardware Development: Digital Fabrication and Advanced Manufacturing; Hardware-Software Systems; Edge Computing and IoT Systems Human-Computer Interaction: Human
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to launch impactful careers. To learn more about the SCALES Postdoctoral Fellowship Program, visit our program page: https://climate.duke.edu/what-were-doing/scales-postdoctoral-fellows-program/ . Key
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education and/or experience. Preferred Qualifications: Professionalism & Confidentiality - demonstrates discretion and sound judgment when handling sensitive information related to trainees, faculty, and
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with Duke policies and procedures to support proper onboarding operations and alignment with institutional guidelines. Manage candidate onboarding data in Smartsheet and University tools, ensuring
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interventions and “nudges” in collaboration with external partners (e.g., companies, nonprofits, policy organizations) • Using advanced data analysis methods to extract interpretable patterns from large, messy
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concepts required. Excellent computer skills with thorough knowledge of Microsoft Excel, Word, and PowerPoint. Supervisory experience is a plus. Email marketing experience in platforms such as Eloqua
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. - Preferred: 2–4 years of experience in research or policy/data analysis related to just energy transitions, including familiarity with Global South energy systems, state-owned enterprises, or transition
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. Responsibilities include statistical analysis, data scraping, and literature reviews, using tools like Stata, MATLAB, Python, and R. Ideal candidates should have a strong quantitative and programming background