578 parallel-and-distributed-computing-phd-"Multiple" PhD positions in United Kingdom
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PhD Studentship: Artificial Intelligence for Building Performance – Optimising Low-Pressure Airtightness Testing Supervisors: Dr Christopher Wood (Faculty of Engineering) and Dr Grazziela Figueredo
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How many positions: 1 Open to Uk students This 3.5 year PhD is fully funded for home students; the successful candidate will receive a tax-free stipend set at UKRI rates (£20,780 for 2025/26) and
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are invited to undertake a three-year PhD programme in partnership with industry to address key challenges in on-platform manufacturing engineering. The successful candidate will be based at the Rolls-Royce
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Human Behaviour in projects targeting social good. Research at N/LAB focuses on the development and application of innovative computational methods using Big Data, Behavioural Science and Machine Learning
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application for your preferred PhD programme must be submitted by 13 January 2025. You must submit your research council funding application by the given deadlines: AHRC North West Consortium Doctoral
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constructed to support the researcher as the PhD progresses with specific courses aimed at the different phases of a PhD. For example, the programme includes aspects such as research methods, technical report
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to funding restrictions this PhD position is only available to UK nationals. As this position is sponsored by the MTC, any successful candidate would need to pass the sponsors own security checks prior
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funding restrictions, this is only available to those eligible for UK fees. How to apply: All applications should be made online via the above 'Apply' button. Under programme name, select Sport Exercise and
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Supervisors: Dr Christopher Wood (Faculty of Engineering) and Dr Grazziela Figueredo (School of Computer Science) External Partner: Build Test Solutions Ltd (BTS) Start Date: 1st October 2025
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. The integration of AI into hardware not only enhances performance but also reduces energy consumption, addressing the growing demand for sustainable and efficient computing solutions. This PhD project delves