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Project Overview This PhD project focuses on the development of robust, low-cost, and compact laser delivery systems tailored for next-generation quantum sensors. These systems are essential
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used. AI methods for generating regulatory hypotheses between genes, hormones and physical properties will also be developed. Applicants must have/be close to obtaining a PhD or MPhil in Computational
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ITP Aero Funded PhD – Characterisation of thin sheet and foil material behaviour for aerospace forming applications Applications are invited for a PhD position at the University of Nottingham
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Research Assistant/Associate in Photonics Integration of Graphene and Related Materials (Fixed Term)
on integrated GRMs. The successful candidate will hold a PhD (or be close to obtaining) in Applied Physics, Material Science, Nanotechnology, Chemistry or Electrical Engineering with experience in photonics
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motivated individual who will thrive in a friendly and supportive group. Candidates must hold a PhD degree (or equivalent) due to be complete within 6 months in neuroscience, psychiatry or a related field
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Institute of Photonic Technologies to be undertaken within the College of Engineering and Physical Sciences at Aston University. Financial Support This studentship includes a bursary to cover the fees rate
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Application deadline: 15/08/2025 Research theme: Computer Science No. of positions: 1 Eligible for: UK This 4-year PhD project will be funded by DLA studentship and is open to UK students
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; EPSRC Centre for Doctoral Training in Green Industrial Futures | Edinburgh, Scotland | United Kingdom | 3 months ago
This is a fully-funded 4 year PhD offering an annual tax-free stipend of £20,780, tuition fees and an enhanced research and training grant. This PhD is one of a number of projects hosted by
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, via the admissions portal (accessed via the 'Apply' button above) by midnight (23:59 GMT), 19th August 2025. On the ‘Choosing a programme’ page, please select (Neuroimaging) Research MPhil/PhD (Full
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critical to ensuring the longevity and safety of fusion reactors. This PhD project focuses on developing an integrated framework that combines cutting-edge computational models, including Monte Carlo