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but not essential. A strong background in materials science and/or modelling is essential. Experience in machine learning, computer vision, and computer programming is desirable. In addition
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bottleneck in the screening process. This PhD project will address this through deep integration of scanning probe electrochemistry, optical microscopy and machine vision, to develop a system that can
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2025 Reference: RD-PHD-01-LS-MH-25 Project Title: The cost of silage production: measuring the carbon footprint of silage Primary supervisor: Prof. Liam Sinclair Co supervisors: Dr Kate Le Cocq, Dr
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James Entry requirements: A 2:1 honours degree or equivalent international qualification, or a master’s degree in relevant subject (e.g., human nutrition, sports and exercise science/nutrition, human
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and Civil Engineering PhD Research Project Directly Funded UK Students Dr Marco Colombo Application Deadline: 30 September 2025 Details Are you ready to push the boundaries of engineering innovation and
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R&D (6.8% of turnover in 2022) and material science expertise make it an ideal industrial partner. Candidate Profile We welcome applicants with a strong academic background (first or upper second
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short courses in the core subjects of this PhD programme including process intensification and green chemistry. This project is part of the Process Industries: Net Zero (PINZ) Centre for Doctoral training
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implement a combination of metagenomic sequencing techniques to comprehensively characterise baseline levels of microbial pathogens in wastewater and surface water and compare our findings with data
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, breaking etc. This makes traditional methods particularly difficult to generalise based on all these driving factors, whereas this PhD project takes a novel and explainable data-driven approach – equation
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-on experience with real-world SCADA data, industry collaboration with RES Group, and training in high-fidelity simulation environments (OpenFAST, Digital Twin technology). This opportunity is ideal for those