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Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description [Background of the recruitment and description
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transition to a circular society, a society that is not extractive but that systematically reuses its resources. In this PostDoc, you will contribute to visions of a circular future, particularly in an urban
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George Emil Palade University of Medicine, Pharmacy, Science, and Technology of Târgu Mureș | Romania | 2 months ago
. Clin. Med.,2025, 14(19):6752. https://doi.org/10.3390/jcm14196752 Khalifa, M., Albadawy, M. Artificial Intelligence for Clinical Prediction: Exploring Key Domains and Essential Functions, Computer
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 1 day ago
reason why Carolina is one of the leading public research institutions in the country. UNC-Chapel Hill offers postdocs comprehensive medical and vision coverage , paid leave, and benefits and services
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, and UT Dallas Bright Leaders Program. Visit https://hr.utdallas.edu/employees/benefits/ for more information. Special Instructions Summary Important Message 1) All employees serve as a representative
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are highly motivated, have interests in computer vision and neural networks, and want to both contribute to new advances in a field with real world applications. The position is in the Digital Signal
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want to hear from you! Your Job: Work on a wide range of computer vision and machine learning methods and applications focusing on the aspects outlined above, inspired by the needs of societally relevant
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(https://atomicfilmslab.org) and will work closely with the computational, device, and simulation teams, as well as with the education and mentorship teams comprising ASWESOME. This position will inform
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industry to address a shared vision to transform the way medicines are designed and produced. The centre’s programme lies at the intersection of the strategically important areas of life sciences, AI and
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for Horticulture and Phenotyping) team research topics focus on low cost computer vision and machine learning, simulation assisted plant phenotyping and machine learning based data mining for plant biology