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machine learning for plant biology Employer Aarhus University (AU) Location Aarhus, Midtjylland (DK) Salary Competitive Closing date 12 Oct 2026 View more categories View less categories Discipline
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feeds Post-doctorat - Modélisation atomique d'actinides par modèles machine learning - H/F 186 / 669 vacancy Détail de l'offre Description du poste Domaine Matériaux, physique du solide Contrat Post
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COLCOM - Postdoctoral Researcher in Machine Learning for Energy Efficient IoT Networks Employer MOHAMMED VI POLYTECHNIC UNIVERSITY Location Benguerir, Morocco (MA) Closing date 31 Oct 2026 View more
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fellowships in machine learning await. Collaborate, innovate, and thrive! PhD Fellowships in Knowledge-Driven Machine Learning in Norway (8 positions) Apply for this job See advertisement About the positions
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Postdoctoral Research Fellow in AI and epidemiology, shaping global health solutions! Postdoctoral Research Fellow in Machine Learning and Artificial Intelligence in Epidemiology Apply for this job See
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 1 hour ago
, computational analysis, machine learning applications), approximation theory, or mathematical models in biology and/or medicine. Teaching duties for the position can be tailored to the applicant’s
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Position Summary The TARDIS collaboration is actively applying and extending the Monte Carlo radiative-transfer open-science framework TARDIS (https://tardis-sn.github.io/) to model the physics of
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 1 hour ago
strategically position itself for sustained impact, as articulated in the School’s Strategic Plan (https://pharmacy.unc.edu/about/oe/strategic-plan/). Our Vision is to be the global leader in pharmacy and
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this position will work as a member of an interdisciplinary team on research involving the use of statistical and machine learning methods for the development of Immune Digital Twins. There will be
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position will work as a member of an interdisciplinary team led by Dr. Colin Xu on Department of Defense (DoD)-funded research project involving the use of statistical and machine learning methods for