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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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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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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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project offers a unique opportunity to develop autonomous microswimmers, which are bioinspired structures at the micrometre scale that can propel themselves through fluids, mimicking natural swimming
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accuracy is still limited. In contrast, computational fluid dynamics (CFD) models can capture the arc physics and molten pool dynamics, including arc energy transfer and liquid metal convection within
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-state physics, fluid dynamics, solid-dynamics, and fracture/degradation; all in a highly transient and non-linear system. In this project we will extend multi-component, multi-phase field frameworks
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enable more targeted mitigation measures. Your investigation of this research question will be principally numerical, employing computational fluid dynamics to produce high resolution simulations which
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overseas. Training can be provided in computational fluid dynamics, machine learning, and nonlinear dynamics. These skills are highly valued across a wide range of industries. Recent data reveals that Fluid
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The role will develop new AI methods for identifying the instantaneous state of a fluid flow from partial sensor information. The research will couple techniques from optimization and control theory
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Liverpool where, in the School of Computer Science and Informatics, we have an active group of PhD students, postdocs, and academics working at the intersection of Machine Learning, Verification and