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for personnel require alternative solutions, such as moving rolling stock maintenance to daytime on days or periods with less transport demand. The objective of this PhD project is to develop and demonstrate a
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will be grounded in rigorous mathematics coupled with a sound understanding of the underlying earthworm ecology. Bayesian inference methodologies will be developed to estimate where and when behavioural
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Computer vision (3D, detection, classification, segmentation, object tracking). Autonomy, creativity, and interest in real-world AI applications. Interest in agriculture or agri-food. What We Offer
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ecology and oceanography, the project will leverage large existing datasets on (i) the movement of migratory seabirds throughout their annual cycle, available via BirdLife’s Seabird Tracking Database (STD
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ability to evaluate fossil fuel CO2 (ffCO2) emissions is currently limited. ‘Bottom-up’ emissions estimates, based on inventory-style accounting and mobile tracking data, can differ significantly from each
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that actively modulate bone regeneration and tissue healing. Objective 1: To design and optimise an innovative peptide-based delivery system encapsulating osteoanabolic miR cargoes, enabling targeted and
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. Objective 1: Optimise the cryoprinting process for fabricating poly(vinyl alcohol) (PVA) and gelatin GelMA-based structures with interconnected 3D pores and channels to achieve precise control over construct
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manufacturing but also paves the way for scalable and reproducible biomaterial solutions in regenerative medicine. Objective 1: Generation of a database of layer-by-layer images from in situ monitoring
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analysis methods, including mixed-effects survival models and mixed-effects models applied to plant growth; experience within a Bayesian framework is highly desirable. 3. Strong skills in data analysis and
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symposia, school-engagement exercises, and future grant applications. Candidate Requirements The successful applicant will have a strong academic track record in the Social Sciences and/or Humanities. Pre