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data sources to answer important population-level questions that will inform health technology assessment, policy, and practice. The successful PhD student will be embedded within an interdisciplinary
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opportunity to network and work directly with them as part of you PhD programme. Number of awards: 1 Start date: September 2026 Award duration: 3.5 years Sponsor: ESRC JUST Supervisors The core supervision team
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language is not English, you will need to meet the minimum English requirements for the programme, IELTS Academic score of 6.5 (with no less than 5.5 in each component test area) or equivalent
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integration into neural circuits to result in functional, restored behaviour. We will use the fruit-fly Drosophila as a model organism for its powerful genetics and molecular cell biology (e.g. CRISPR/Cas9 gene
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Science and Technology Facilities Council (STFC), Scientific Computing Department Daresbury Laboratory, with the PhD being conducted between Bangor and Daresbury with a 50:50 time split. This project is
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of the candidate Essential requirements: A 1st class or 2.1 degree (or equivalent) in Environmental Science, Remote Sensing, Computer Science, Surveying Engineering, or related field Strong coding skills (Python
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AI techniques for damage analysis in advanced composite materials due to high velocity impacts - PhD
intelligence, particularly in computer vision and deep learning, offer an opportunity to automate and enhance damage assessment by learning patterns from multimodal data. This research seeks to bridge the gap
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require an IELTS score of 6.5 overall with a minimum of 5.5 in all sub-skills. International applicants may require an ATAS (Academic Technology Approval Scheme ) clearance certificate prior to obtaining
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sustainability assessment framework and computational tool using Model-Based Systems Engineering (MBSE) and lifecycle modelling techniques. Apply and test the framework through case studies (e.g., ADR, ISRU, In
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qualification in ecology, marine biology, data science, environmental sciences, or related fields. Candidates with interdisciplinary backgrounds and strong quantitative skills are particularly encouraged