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developing cutting-edge computer vision and deep learning aimed at optimising inspection and monitoring of infrastructure. Applying these advanced technologies to real-world infrastructure challenges through
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developing cutting-edge computer vision and deep learning aimed at optimising inspection and monitoring of infrastructure. Applying these advanced technologies to real-world infrastructure challenges through
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Trust. The successful candidate will work closely with the PI and a PhD student within a larger cross-disciplinary team to construct a quantitative computational model of carbonate biomineralisation
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field. A solid foundation in fluid dynamics and heat transfer, and experience with computer programming and/or CFD are desirable but not essential. The student is expected to present their research
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The project aims to develop a publicly accessible in silico database that identifies and catalogues bacterial genes capable of altering the effectiveness of chemotherapy drugs in colorectal cancer (CRC) patients. Focusing on microbial modification of 5-fluorouracil (5FU), the study will...
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Exciting Fully Funded PhD: Computational Modelling for High-Pressure, Low-Carbon Storage Technologies. Be a Key Player in Shaping the Future of Clean Energy Storage! School of Mechanical, Aerospace
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No of positions: 1 How to apply:uom.link/pgr-apply-2425 This 3.5 year project is funded by the University of Manchester through the Strategic Doctoral Landscape Award (sDLA) Scholarship. The successful candidate will receive an annual tax free stipend set at the UKRI rate (£20,780 for 2025/26)...
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-Stokes equation are not eligible. Solving the BBGK equation is extremely challenging due to the high computational cost originated from its high-dimensionality. As a deterministic method, the potential
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they take part in a residential camp and longer-term mentoring programme created by and for those with an ULD. One strand of the PhD will provide feedback to Reach on the quantitative and qualitative
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health with the aim of creating healthier spaces and habits for them. This is a highly interdisciplinary project that combines computational modelling and behavioural science. The first part will be based