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Field
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, allowing them to add to their existing clinical targets of anxiety and depression disorders, thus developing impact from this research. Methodology This studentship will take a mixed-methods approach to
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Specification We seek an enthusiastic individual who is interested in marine ecology, computing, with some prior experience in programming and data handling, eager to communicate findings to wider stakeholders
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could increase the process build rate, and thus reduce carbon emissions, and uptake for this process across a wide range of sectors, offering solutions not possible by conventional manufacturing methods
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computing and analysis of data will enable the development of control mechanisms that will overcome one of the major barriers for exploiting the benefits of hybrid propellant propulsion systems. The project
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The University of Exeter’s Department of Computer Science is inviting applications for a PhD studentship funded by Faculty of Environmental Science. For eligible students, the studentship will cover
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will be key to ensuring that useful measurements, methods and representations are developed. In particular, the project will support designers to achieve driver and passenger experiences that surpass
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, embrittlement, and cracks. This will be achieved by integrating ultrasonic arrays with inverse modelling methods to interpret historical data. Additionally, the project will explore the failure mechanisms
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world introduces new challenges. Attackers equipped with quantum computing capabilities will be able to break traditional cryptographic systems, rendering them obsolete and posing a significant threat to
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to obtaining their visa and to study on this programme. We have three possible start dates for this studentship - January 2026, April 2026 or September 2026. Please note your preference in your application form
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The funding provider: Health Data Research UK Subject areas: Wider Data Science Field, Maths and Computer Science Project start dates: 1st October 2025 ** (Please see the note below regarding