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Field
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The overarching aim of the project is to understand how early neurodevelopmental risk factors disrupt brain maturation and contribute to psychosis vulnerability across development. This PhD project
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Reference: RD-PHD-01-VP-MH-25 Refining the feeding value of rye for broiler chickens (PhD project) Primary supervisor: Professor Vasil Pirgozliev, Department of Agriculture and Environment Non-academic
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About the Project WE ARE RECRUITING four PhD students to start in October 2025. Each 4-year studentship is generously funded with an enhanced stipend, all tuition fees covered, and research support
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on previous interventions of pneumonia. Who is this PhD suitable for? This PhD is suitable for a hard-working researcher with an interest in respiratory infections and health economics. Essential skills: A
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Deadline: All year round How to apply: uom.link/pgr-apply-2425 How many positions: 1 Open to: UK students This 3.5-year PhD project is fully funded by The University of Manchester and the funding is
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Application deadline: All year round Research theme: Systems and Control How to apply: uom.link/pgr-apply-2425 This 3.5 year PhD project is funded by The School of Engineering and is available
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. Applying machine learning to New Zealand’s landslide inventories to model landslide location, character and dynamics. Integrating time-series and inventory data to develop new models to predict location
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Research theme: Textiles How to apply: https://uom.link/pgr-apply-2425 How many positions: 1 This 3.5 year PhD project is funded by The University of Manchester and an industrial partner and the
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health monitoring, supporting studies in military aircraft systems. Engaging with these facilities allows students to acquire practical skills and technical expertise, enhancing their research capabilities
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; EPSRC Centre for Doctoral Training in Green Industrial Futures | Edinburgh, Scotland | United Kingdom | 3 months ago
, further exploring the carbon-related impact of polymer breakdown. The project will also incorporate artificial intelligence (AI) and machine learning to optimise degradation processes and data analysis