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website: https://rwjms.rutgers.edu/research/inspire/home. Must take part in all of the research, writing and teaching training provided for INSPIRE IRACDA Fellows. Must take part in all of the research and
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, or machine learning) Experience working with various animal models Ability to work in an interdisciplinary research environment Specific Requirements Programming experience (Python and R) Experience with
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. About the role As Postdoctoral Researcher in Big Data for Cardiovascular Population Health, you will play a key role in applying machine learning, health statistics, and large-scale medical and population
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Science, or Information Science, with no more than five years post receipt of the PhD. The position requires experience with at least one of the following: Data Science, Machine Learning, Computational Social Science, Big Data
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qualifications. Our benefits include: • Generous employer contribution pension • 29 days annual leave plus bank holidays, along with Christmas closure • Ride to work and EV car scheme available For more
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employer contribution pension • 29 days annual leave plus bank holidays, along with Christmas closure • Ride to work and EV car scheme available For more information, please see University of Manchester
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opportunities to develop scientific independence, establish new research directions, collaborate across disciplines, mentor junior scientists, and acquire the skills and publication record necessary for the next
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machine learning aspects of this AI-assisted semantic tagging and fuzzy logic search tool. The Postdoctoral Researcher on the project will work on a project related to an aspect of the hip-hop-specific
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framework for understanding emergent deception in human-AI interaction by uniting behavioural-psychological, economic-strategic, and machine learning perspectives. The postdoc will be jointly supervised by
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Organization National Energy Technology Laboratory (NETL) Reference Code NETL-FRP How to Apply Please visit https://orise.orau.gov/netl/ to learn more about the program and the application process