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Yannitell Reinhardt, who will jointly supervise the postdoctoral research with Prof Philip Leifeld (University of Manchester). Duties of the Role You will study the policy networks enabling or hindering
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Current University of Arkansas System employees, including student employees and graduate assistants, need to log in to Workday via MyApps.Microsoft.com , then access Find Jobs from the Workday
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the way. We’ve built the world’s largest workspace network so that our customers can work from wherever, and however, they want… in over 120 countries across the globe! Join us and help us bring more
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University of North Carolina at Greensboro | Greensboro, Indiana | United States | about 24 hours ago
, and affordability. UNCG is ranked No. 1 most affordable institution in North Carolina for net cost by the N.Y. Times and No. 1 in North Carolina for social mobility by The Wall Street Journal — helping
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(https://portal.findresearcher.sdu.dk/en/persons/ ). Eligibility: Applicants have to find a supervisor at SDU Mobility Rule: Applicants must not have lived, worked or studied in Denmark or at SDU
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the network and strengthen the value chain. By building on what works and tapping into unused potential, the project aims to co-design scalable, locally appropriate solutions. This approach will also be adapted
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conferences. The postdoc will benefit from ETH Zurich’s strong interdisciplinary and global network, including: The Albert Einstein School of Public Policy, The ETH’s Energy Science Center and ETH's World Food
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Current University of Arkansas System employees, including student employees and graduate assistants, need to log in to Workday via MyApps.Microsoft.com , then access Find Jobs from the Workday
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machine learning and network biology. Background in cancer research. Pay Range: $62,232.00 - $81,000.00 To apply visit https://academicjobsonline.org/ajo/jobs/31509 and submit a cover letter, full CV, and
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Description Join the NWO Perspectief FIND program and develop methods to adapt Transformer-based foundation models for defect detection where data is scarce and unlabeled. Explore few-shot learning, self