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the rich, unstructured information found in clinical notes and cannot effectively gather data on lifestyle and social determinants of health. This PhD project will pioneer a novel, hybrid AI framework
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Primary supervisor - Dr Dominic Cram This exciting PhD will examine how parental age and the social environment interact to shape offspring health in a wild mammal, by combining epigenetic
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multi-disciplinary team Strong communication skills, both written and verbal Qualifications PhD Awarded (for the position as Research Associate) in Mathematics or Statistics or Computer Science
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patient care, and the project will provide the student with a valuable skillset in interdisciplinary research, encompassing bioinformatics, (meta)genomics and statistics with clinical relevance
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to alternative splicing. This PhD offers the scope to develop independence – pursing promising leads on interesting biology – while addressing one of evolution’s most longstanding challenges. Beyond advancing
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interdisciplinary training in plant genomics, bioinformatics, and statistical modelling, as well as practical skills in horticulture, experimental design, and data analysis. Working in the De Vega Lab at the Earlham
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scope to adapt some elements of the PhD to their interests. There will also be opportunities to join related project teams in long-term condiWe are seeking a motivated and compassionate student with a
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problems) and qualitative (structure of level sets) questions in spectral geometry. Our Community You will be joining an outstanding, impactful department of mathematics and statistics. 98% of our research
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; biogeochemistry and fisheries modelling). The PhD candidate will acquire and/or strengthen their understanding of interdisciplinary working, modelling and statistics applied to economics, trade-off analysis skills
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patient samples. The Sheffield arm of the project will develop statistical and machine learning models to identify and validate predictive biomarkers of resistance evolution in Pseudomonas aeruginosa lung