Our existing multi-disciplinary research strengths concern mathematical applications in the biomedical and life sciences, engineering, computing and industry, and include: bioinformatics and computational statistics; computational neuroscience and network science; mathematical modelling and analysis of PDEs; deep learning and biomedical image analysis; and quantum information science. To complement our strategic aims and teaching excellence, research or scholarly activity in pedagogy is also of interest.

The successful candidate will also have excellent communication and presentation skills, being capable of teaching foundation, undergraduate and postgraduate students across our portfolio of Mathematics courses, and of supervising student projects or dissertations up to and including those at Masters and PhD level. For this post your teaching interests should align with one or more of the broad topic areas that contribute to our existing BSc / MMath Mathematics, BSc Financial Mathematics or BSc Data Science courses.

Research in the School of Science and Technology is extremely strong in terms of high-quality outputs, funding income, and international impact. A key strength of the School is its collegial, multi-disciplinary approach with mathematicians, statisticians, scientists and engineers collaborating extensively. Our teaching aims to be exciting, innovative and relevant and is highly regarded, with Mathematics performing consistently well in the National Student Survey.

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