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Field
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environment and impact with the QR funding allocated for the Faculty of Arts, Business and Social Sciences (FABSS). The plan is to support 0.6fte post-doctoral research fellowships under this scheme. With a PhD
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software such as recommendation systems, computer-aided decision support systems Previous experience with using deep learning models (e.g., convolutional neural networks, autoencoders, transformers
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presentation Human study experience Skills in the development and running of analytical assays Desirable criteria Skills in product design and operating on computer-aided design CAD software e.g. Fusion 3D
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product design and operating on computer-aided design CAD software e.g. Fusion 3D Experience in additive manufacturing particularly vat polymerization. Downloading a copy of our Job Description Full details
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Modernising Medical Microbiology (MMM) unit at the University of Oxford (https://www.expmedndm.ox.ac.uk/mmm). You will be joining a highly interdisciplinary team of approximately 40 clinicians, computational
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The Faculty of Mathematics at the University of Vienna is the largest Austrian institution of mathematical research and tertiary education in the mathematical sciences. It consists of active research groups in
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applicant. Access to high-performance computing facilities and cloud-based quantum hardware will be provided to support simulation and verification of theoretical methods. About you The successful candidate
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College of Chemistry and Molecular Engineering, Peking University | Exeter, England | United Kingdom | about 22 hours ago
) Location: Department of Engineering, University of Exeter The Role The Faculty of Environment, Science and Economy seeks a Postdoctoral Research Associate to join the ARIA-funded NEUROBOT project
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The Department of Earth Sciences are seeking a highly motivated and skilled researcher responsible for conducting a comprehensive retrospective analysis of volcanic seismicity across Costa Rica’s
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of Engineering Science. The post is funded by EPSRC and is fixed term to the 31st January 2027. A2I explores core challenges in AI and machine learning to enable robots to robustly and effectively operate in complex, real