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Research Office Location: Newport, Shropshire TF10 8NB Post Type: Full Time Contract Type: Fixed Term - 36 Months Closing Date: 23.59 hours GMT on Sunday 01 March 2026 Reference: PHD-SELF-APRIL
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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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2025 Reference: RD-PHD-02-LS-MH-25 Project Title: Dietary strategies to reduce methane production in dairy cows and their effects on the rumen microbiome and metabolism Primary supervisor: Prof. Liam
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Modern numerical simulation of spray break-up for gas turbine atomisation applications relies heavily upon the use of primary atomisation models, which predict drop size and position based upon local gas/liquid phase conditions. Whilst direct simulations of breakup are possible, computational...
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Using capturing carbon dioxide and clean hydrogen is essential for a sustainable future in energy and chemical production. However, the transition is hindered by a lack of efficient, affordable catalysts. This EPSRC-funded project leverages cutting-edge X-ray spectroscopy to unlock how alkali...
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suggest hypotheses for therapeutic targeting. This PhD studentship is part of the LifeArc ARDT, a UK-wide £12m partnership between Newcastle, Birmingham, and Belfast to accelerate rare disease trials
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to rare disease trials. This PhD studentship is part of LifeArc ARDT, a UK-wide £12m partnership between Newcastle, Birmingham, and Belfast to accelerate rare disease trials. Students will receive training
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high-priority condition as new disease-modifying therapies are developed. This PhD tackles a key diagnostic bottleneck in ADTKD-MUC1 and integrates precision genomic medicine into routine kidney care
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Apply online now: https://karriere.klinikum.uni-heidelberg.de/index.php?ac=application&jobad_id=25655 PhD Student – Bioinformatics/ Computational Biology (m/f/d) Stellenanzeige merken Stellenanzeige
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early ‘prodromal’ stages) is yet to be established in large community settings. This PhD project will examine the effectiveness of AI-based analysis of eye images in predicting cognitive/neurodegenerative