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PhD Scholarship in Big Data and Analytics for Crop Genetics Modern agriculture and biomedical research are driven by the availability of big data and the development of data science. The recent
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analytical imaging methods, then working with collaborators to apply these methods to biomedical research, diagnostic imaging and beyond. Research projects vary from purely theoretical, to computational
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the development of numerical methods for astorphysical fluid dynamics and radiation transport. Projects may employ a range of approaches from analytic modelling and numerical calculations on desktop
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semi-analytical upscaling techniques allow handling diffusive-dispersive fluxes but are not applicable to kinetics non-equilibrium models. The asymptotic technique developed for relaxation systems allows
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. The successful candidate will: Demonstrate strong analytical and research capability Demonstrate capability in design or creative-practice research Show interest in interdisciplinary and field-based research in
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research publications Possess excellent written and verbal English skills Demonstrate strong laboratory and analytical capabilities Have experience in concrete technology, cement chemistry, materials science
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analysis, case studies) Strong analytical and writing skills Desirable Skills Familiarity with energy, water, food or waste policy domains Experience with Multicriteria Mapping Interest in interdisciplinary
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qualitative data capture and analysis Ability to work independently and manage tasks with minimal supervision Strong organisational and analytical skills Excellent communication and collaboration skills
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linked-data cohorts, the National Centre for Healthy Ageing Data Platform and the 45 and Up Study, to develop analytical tools that can identify older adults at elevated risk of PRAC entry. A central focus
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equivalent qualifications) • Basic knowledge of analytical techniques of rock characterisation • Prior experience in experimental geochemistry (water-rock reactions) is preferred • Some knowledge of