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within applied mathematics, materials science, physics and building science. Mathematical statistics is an important part of these four areas of research. Relevant applications include machine learning
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Apply and key information This project is funded by: Department for the Economy (DfE) Summary This PhD project offers an exciting opportunity to develop next-generation biocomposites made from
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to prepare project reports and co-author research papers. The ideal candidate is expected to be working towards a PhD in Computer Engineering, Computer Science, Computer Systems Engineering, Electronic
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Missouri University of Science and Technology | Rolla, Missouri | United States | about 18 hours ago
, among the finest facilities on the MU campus. Featuring state-of-the art technologies, Cornell Hall includes 17 classrooms, three computer labs, an executive classroom, an active learning classroom, a 500
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application! We are looking for a research engineer within the Division of Statistics and Machine Learning (STIMA) at the Department of Computer and Information Science. In this position, you will have the
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in foundational neural models that learn from large unlabeled image datasets, also incorporating context from additional data such as wireline logs or well reports. You are suited for this position
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information exchange (HIE) Natural language processing in clinical/biomedical domains Mobile health, digital health, human–computer interaction in health Learning health systems, community health informatics
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more information see: http://www.mn.uio.no/english/research/phd/ All candidates and projects will have to undergo a check versus national export, sanctions and security regulations. Candidates may be
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and computational physics High-energy physics/astrophysics/cosmology Statistical mechanics/complex systems/non-linear physics Machine learning/first-principles calculations/large-scale simulations
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project The main objective of this PhD project is to explore and analyze bio-inspired neural architectures for early detection from spatio-temporal data under realistic sensing and computational constraints