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Field
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requirements for our PhD programme . Candidates should have a strong background and first degree in chemistry or pharmaceutical sciences or a closely related subject (BSc/MChem/MSc). Industrial experience
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will be jointly supervised by: Dr Dominik Leichtle, School of Informatics, University of Edinburgh Dr Elham Kashefi, School of Informatics, University of Edinburgh Dr Theodoros Kapourniotis, National
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Deadline: 31 August 2025 A fully funded 3.5 year PhD position is available to work on the project titled “Scalable benchmarking for digital quantum computers based on blind testing”. This position
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This 3.5-year PhD is fully funded; the tuition fees are paid and you will receive an annual tax free stipend set at the UKRI rare (£20,780 for 2025/26). The funding is linked to UK Research and
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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
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effort between School of Engineering and School of Chemical Engineering at Aalto University supported by our industrial partners. The PhD student to be jointly supervised by two supervisors; Prof. Hamid
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covers tuition fees, a stipend, and RTSG (research training and support grant). Alongside the scientific PhD training, the programme will provide a wide range of training opportunities. DTP Standard
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covers tuition fees, a stipend, and RTSG (research training and support grant). Alongside the scientific PhD training, the programme will provide a wide range of training opportunities. DTP Standard
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of the largest Statistics departments in the world, with a thriving PhD programme and a long-established reputation for research activity of the highest quality, enhancing both the PhD student experience and the
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This self-funded PhD opportunity sits at the intersection of several research domains: multi-modal positioning, navigation and timing (PNT) systems, AI-enhanced data analytics and signal processing