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the university and with industry to translate discoveries into clinical proof of concept studies. Working with a team led by Drs. H. Kim Lyerly, Zachary Hartman and Josh Snyder, this program spans basic discovery
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will also use these results to aid in the testing, evaluation and transition of technologies developed by government-funded research programs. Identify opportunities to apply AI to improve existing
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one of the world’s leading centres for additive manufacturing research and development, invites applications for a fully funded PhD programme. Metal additive manufacturing is transforming how complex
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in the field of educational sciences, with a focus on GenAI, reading comprehension, feedback, and self-regulated learning (SRL). This 4-year PhD project is situated within a broader research programme
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. This project is aligned with the “Dialling up Performance for on Demand Manufacturing” Programme Grant, which will place the student within an active and supportive team of 9 other PhD students, 15 postdoctoral
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PhD Studentship available on the RAINZ CDT programme at the University of Oxford. Project Overview Abstract: Nuclear facilities require regular inspection to monitor specific locations (for example
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computational chemistry or physics will be preferred, but candidates with a solid background in statistics, computer science, and/or mathematics are also encouraged to apply. Programming skills (e.g., Python
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Strong research background in fluid dynamics and/or magnetohydrodynamics Excellent programming and numerical skills (in addition to core IT skills) Proven ability to analyse data and write-up results
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will also use these results to aid in the testing, evaluation and transition of technologies developed by government-funded research programs. Identify opportunities to apply AI to improve existing
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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