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Field
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, Economics, Business Analytics, Data Analytics, Energy Finance, Accounting, or a related field is desirable. Experience with empirical research methods and programming languages such as Python, R, Stata
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, but its human burden is badly understood. This PhD addresses this gap, integrating multiple high‑value datasets describing metagenomic and metatranscriptomic sequencing information, clinical and
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, analytical chemistry and enzymology. Working in an enthusiastic and supportive team the student will become expert in state-of-the-art (bio)chemistry, biophysics and photocatalysis. They will also expand
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ownership of the project, shaping experimental design, developing new approaches, and driving the research with increasing independence. By integrating laboratory, analytical, and field-based methods
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simulations run on world-class supercomputing facilities alongside AI algorithms and data analytics tools, and share your results with experimental collaborators. The position is part of the Research Council
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where possible validation data will be taken from industrial and openly available literature. The successful candidate will gain experience in computational, analytical and experimental approaches across
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advanced simulation, AI-ready modelling and industrial data to accelerate pharmaceutical manufacturing and the delivery of life-saving medicines? This industrially focused project, co-supervised by
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Studentship Information Supervisor: Dr Hannah Cooper (UoN) Secondary Supervisor: Dr Nicholas Girkin (UoN), Dr Georgina Barratt (BBRO) Subject Area: Sustainable Agriculture and Climate Resilience
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discipline such as statistics, mathematics, computer science, engineering, data science, or a related biomedical/population health subject. Applicants should have strong analytical and programming skills (e.g
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experimental laboratory skills with an interest in working alongside advanced computational and analytical technologies. Experience in interdisciplinary research and collaborative science is highly desirable