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technology and computer science Need help understanding the process? Visit our scholarship guide Application How to apply You must submit an application and include: Personal statement addressing the purpose
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This 3.5-year PhD studentship is open to Home (UK) applicants. The successful candidate will receive an annual tax-free stipend set at the UKRI rate (£21,805 for 2026/27; subject to annual uplift), and tuition fees will be paid. We expect the stipend to increase each year. EU students with...
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This 3.5-year PhD project is fully funded by industry, and home students are eligible to apply. The successful candidate will receive an annual tax-free stipend set at the UKRI rate (£21,805 for 2026/27) and tuition fees will be paid. We expect the stipend to increase each year. The start date...
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compensation plan: tax advantages contracting some products (health insurance, childcare, training, among others.) Training activities: languages, mentoring programme, wellbeing programme. International
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our Postgraduate Research Society (PGES) and our PGR Research Group Reps to enhance the research environment for PGRs. PGRs benefit from training through the Researcher Academy’s Training Programme
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Research Assistant to investigate digital reading comprehension through large-scale data analysis. This role, funded by the John Fell Fund, sits at the fascinating intersection of computational
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of Marts 2026 Successful candidates will be asked to send an application to the PhD Secretariat, Faculty of Health Sciences, to be enrolled as PhD students. The PhD programme will be carried out in
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The PhD project aims to develop dynamic pressurisation techniques for real-time crystallography and spectroscopy studies of samples in a liquid environment. It will be used for in-house macroscopic measurements and integrated into multiple national central facilities, including the Central Laser...
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nursing, medicine, pharmacy, geriatrics care, medicines safety, health care communication, digital health, and health care sociology. Refer to www.research.monash.edu/en/persons/elizabeth-manias for main
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. Experience in programming (in particular, Python) and an interest in machine learning, data analysis, or scientific computing are expected. Prior experience with machine learning or optimization methods is