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Fully Funded PhD Research Studentship tax-free stipend of £20,870 Design, Informatics and Business Fully Funded PhD Research Studentship Project Title: Autonomous AI-powered red agents for enhanced
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of Strathclyde will lead the wind energy training and research elements of the programme. Funded by EPSRC, this 4 year PhD studentship, at the University of Strathclyde is in the area of novel wind turbine concept
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European Centre for Environment and Human Health in the Faculty of Health and Life Sciences at the Penryn Campus in Cornwall. Measures taken in the built environment to reduce energy consumption (to help achieve net zero goals) can impact on the indoor environment and have positive or negative...
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to apply, please use the below Programme Application Portal to get in touch with the Programme Admission Admin. Application received in other channels will be re-directed and requires apply for a second time
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Resilience (WIRe) , a prestigious collaboration between Cranfield University, the University of Sheffield, and Newcastle University. The WIRe programme offers bespoke training that hones both technical and
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Fixed-term: The funds for this post are available for 1 year. Applications are invited for a Research Associate (Postdoc) to join the Prorok Lab in the Department of Computer Science and Technology
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suitable to candidates with a wide range of backgrounds such as but are not limited to: climate science, psychology, mathematics, geography, environmental science, law, computer science, public health
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Liverpool where, in the School of Computer Science and Informatics, we have an active group of PhD students, postdocs, and academics working at the intersection of Machine Learning, Verification and
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Research Assistant/Associate in Photonics Integration of Graphene and Related Materials (Fixed Term)
optoelectronics, light emission, optical sensing and quantum communications. This is an ambitious research program, with a strong interdisciplinary nature, across photonics, plasmonics, device physics, electrical
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your suitability with evidence of the following: Have backgrounds in computer science (or engineering), system engineering, or physics/mathematics. Knowledgeable in machine learning techniques (had