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genomics, evolutionary biology, bioinformatics and population genetics. They will develop skills in large-scale data analysis and scientific programming. The student will take part in journal clubs and
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lead to the allocation of energy and nutrients towards AMR instead of biomass growth. This PhD project will unravel the mechanisms driving AMR in pioneer and extreme soil environments in the Arctic
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represent the research group at external seminars and conferences. To be considered, you must hold a PhD/DPhil in statistical genetics, quantitative genetics, bioinformatics, computer science, statistics
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to effectively drive biodegradation traits into contaminated soil communities. Methodology The successful applicant will use a combination of molecular and environmental microbiology, bioinformatics and
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High-in-demand technical (bioinformatics, molecular genetics, microbiology, phenotype engineering) and transferrable (critical thinking, ethics, Open Research) skills. Embedded in thriving, respectful
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genetic adaptations (‘genetic swamping’). Training The student will receive broad training in molecular biology, historical DNA, genomics, bioinformatics and population genetics. The student will take part
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, bioinformatics, and statistical modelling in R. You will also gain experience in critical thinking, scientific writing, and presenting your research. Transferable skills for academic and non-academic careers will
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to training courses, seminars, and mentoring opportunities. You will also work closely with Dr Ellen McDonagh's team at Open Targets / European Bioinformatics Institute. You should have strong organisational
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3 Year, full-time funded PhD Studentship Eligibility: Home UK/EU and International applicants Bursary p.a.: Bursary equivalent to UKRI national minimum stipend plus fees (current 2025/26 bursary
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health, and bioinformatics. You will apply advanced AI methods - from classical machine learning to large language models and agent-based AI - on large-scale healthcare datasets, including structured