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Field
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, monitor financial activity, perform reconciliations, and provide budget forecasts and variance analyses. Advise department leadership and faculty on financial planning, resource allocation, and account
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and Intelligent Systems Research Group. The research groups consist of around 30 full- and part-time faculty members and several postdoctoral researchers and PhD students. The research groups conduct
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We are seeking to appoint a Senior Postdoctoral Researcher in Statistical Machine Learning and Deep Generative Modelling to apply and develop cutting- edge deep generative probabilistic models
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for faculty, postdoctoral fellows, and graduate students. The role is responsible for ensuring accurate financial stewardship from award setup through closeout, including monitoring expenditures and cost share
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forecasting reports for all researchers. Review individual projects, approaching deadlines, and possible adjustments needed to keep budgets on track and in compliance with guidelines. Process division funding
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- and part-time faculty members and several postdoctoral researchers and PhD students. The research groups conduct research in various areas of mobile network systems, multimedia and AR/VR/XR systems
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larger project team and a cohort of PhD research fellows and postdoctoral researchers across NTNU, the Fridtjof Nansen Institute and the University of Oslo. The position offers excellent opportunities
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collaboration with the PI and Laboratory Administrator, develops and implements research and financial plans, long-range financial forecasts and strategies for utilizing existing resources and identifying
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 months ago
Posting Information Posting Details Department Epidemiology - 463501 Posting Open Date 08/29/2025 Application Deadline Open Until Filled Yes Position Type Postdoctoral Scholar Position Title
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to measure, interpret, forecast, and intervene in infectious disease systems has grown dramatically. CIDD is committed to leading cutting-edge modeling and computational approaches to leverage the breadth and