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international equivalent, in computer science, artificial intelligence, data science, human-computer interaction, psychology, organisational psychology, business analytics or a closely related subject. A relevant
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in programming for data analysis and algorithm development (e.g. Python, MATLAB). Strong analytical skills and the ability to critically evaluate technical and scientific literature. Excellent
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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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design and test enzyme variants, develop biochemical and analytical assays to measure performance, and investigate how combinations of enzymes can work together to maximise plastic depolymerisation
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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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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