2,630 data-"https:" "https:" "https:" "https:" "https:" "UCL" "UCL" positions at Duke University in United States
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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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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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skills are particularly welcome. For information about the lab and the PI, please visit: https://www.cellbio.duke.edu/purushothama-rao-tata/ . This will be a minimum one-year appointment, contingent upon
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organizational skills with the ability to manage multiple priorities and meet deadlines. • Proven ability to handle confidential information with discretion and professionalism. • Excellent verbal and written
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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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Program, and the field site in Kenya, and engage with investigators at all sites across various disciplines. The project will focus on conceptualizing, innovating, and implementing data-driven approaches
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benefits, and a culture that values diversity and professional growth. Learn more about our benefits at https://hr.duke.edu/benefits . Anticipated Pay Range: $44,766.00 – $71,706.00 annually, based
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contributions of social determinants of health (e.g. healthcare access, socio-economic status, systemic racism) and molecular mechanisms that drive cancer mortality. Leveraging robust data from primary and
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. The projects seek to improve our scientific understanding of memory function by investigating (a) the nature of mnemonic representations using cutting-edge representational similarity analyses (RSA) of fMRI data