985 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "NORTHUMBRIA UNIVERSITY" research jobs in United Kingdom
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relations in space Sustainability and management of orbital space An engaged scholarship approach will be taken to the research, with the post holder involved in rigorous academic and industry collaborations
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manufacturer. Based on our publication (ACS Appl Nano Matter 2022, 10.1021/acsanm.2c03406) and our ongoing collaborative work, we have developed a new chemical assay coupled with a machine learning algorithm to
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holder must have: Expertise in advanced theoretical and computational electromagnetics, including high frequency asymptotics. Expertise in artificial intelligence and machine learning. Recent research
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Digital Twin Framework for Smart and Sustainable Advanced Manufacturing Research area 3: Advanced Multifunctional Materials The ideal candidates would have a background in machine learning, manufacturing
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• A comprehensive range of childcare services • Family leave schemes • Cycle and electric car loan schemes • Employee Assistance Programme • Membership to a variety of
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language processing for accessible science to contribute to the Terminology-Aware Machine Translation for Accessible Science (TaMTAS) project. The project is funded by EPSRC under the CHIST-ERA Call 2025: Science in
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this information-gathering process. The successful applicant will have strong expertise in programming, and in particular developing AI-based computer vision methods. Ideally, they will have experience
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experience in the use and/or development of machine learned interatomic potentials would be seen as a significant asset. Previous experience of inelastic neutron scattering spectroscopy (or similar) would be
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systems, and subsystems, particularly rotating machines. Data Science – handling and processing large data sets (experience across multiple domains welcome). Research in Artificial Intelligence – including
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will contribute to the project’s research agenda by helping to identify collect, acquire, clean, and manage datasets on ownership of U.S. and European public and private firms, conducting sophisticated