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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 1 day ago
Proposed Start Date 03/16/2026 Estimated Duration of Appointment 12 Months Position Information Be a Tar Heel! A global higher education leader in innovative teaching, research and public service
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methods. In the latter case, estimates and causal inferences will be made, and natural experiments will be analysed using econometric techniques. The project also includes dissemination activities and the
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theorem provers such as Coq or Isabelle/HOL. Proof Automation. We plan to develop formal methods for automatic reasoning that can be materialized into commercial tools. Responsibilities Participate in and
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be in charge of finishing ongoing projects in the group, involving the development of probabilistic methods for the identification of non-coding cancer driver elements and of the tumor mode of growth
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partner, POST Luxembourg , one of the country's largest employers and a leading provider of postal, telecom, ICT, and financial services. The successful candidate will join the Computer Vision, Imaging, and
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will join a dynamic, interdisciplinary team focusedon developing and applying novel AI and statistical methods for multi-omics data analysis. This position offers a unique opportunity to work at the
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more about our benefits and what it is like to work at SLU at https://www.slu.se/en/about-slu/work-at-slu/ Development of statistical methods for estimating plant population size and change Mathematical
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based in the research group “Historical Building Research” (Head G. Styhler-Aydın) of the Department of Historical Archaeology (see https://www.oeaw.ac.at/en/oeai/research/historical-archaeology
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are in compliance with the necessary trainings (both at the lab and at the institutional level). Minimum Education and Experience: A PhD degree in Computer Science, Electrical/Computer Engineering, or a
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of computer and relevant programs (Microsoft Word, Excel, PowerPoint, etc.). Communication and organization skills. Experience with flow cytometry, ELISA, proteomics, or other related molecular methods