Biological systems are extraordinarily complex. Protein-protein interaction networks, gene regulatory networks, metabolic networks and other molecular interaction systems contain enormous numbers of components and interactions, and their organisation is both far from random and far from regular. Their networks exhibit hierarchy (a few nodes with many connections and many nodes with few), homophily (nodes which are more “similar” are more likely to connect), modularity and other forms of structure that emerge from the underlying biological processes governing how components interact. But only recently have methods been proposed to measure network complexity directly and parsimoniously.

So, how statistically complex are biological networks? What mechanisms generate this complexity? And, critically, how is this network complexity related to biological function and evolutionary history?

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The Department is at the forefront of developments in machine learning, data science, and computational methods for understanding complex biological systems, integrating these approaches into both its research and teaching. This role offers significant scope to shape the future of bioinformatics and quantitative biology at Oxford and beyond.

You will be expected to develop and lead a world-class research programme in bioinformatics, helping to strengthen Oxford's position in areas such as statistical genomics, computational biology, machine learning for biological data, engineering biology, systems biology, and biomedical data science. We value the breadth of approaches that contribute to modern bioinformatics. Whatever your particular focus, you will understand how quantitative and computational methods can be applied to important biological and biomedical questions, and how collaboration across disciplines can generate new insights and opportunities. Alongside your own research, you will support the development of doctoral students, postdoctoral researchers, and early-career academics. You will contribute to our teaching at undergraduate and postgraduate level, delivering lectures, supervising student projects, and supporting graduate research students.

We are looking for someone who combines scholarly distinction with a collaborative and ambitious approach to research. You will be a researcher with an international reputation in bioinformatics, with a strong record of producing influential research at the interface of statistics, computational biology, genomics, and data science, and of securing research funding. Your work should advance the field, whether through methodological innovation, biological discovery, or the development of new approaches to understanding complex biological and biomedical data. You will bring experience of shaping research strategy, building productive collaborations, and exercising academic leadership. Above all, we wish to appoint someone who shares our values of intellectual curiosity, academic excellence, scholarly integrity, and a commitment to fostering a positive, supportive, and inclusive environment for all.

If you would like to discuss this post, please contact the Head of the Department of Statistics, Professor Frank Windmeijer, frank.windmeijer@stats.ox.ac.uk, or for information about University College please contact the Senior Tutor, Dr Andrew Bell, andrew.bell@univ.ox.ac.uk. All enquiries will be treated in strict confidence and will not form part of the selection decision.

The closing date for applications is 12:00 noon UK time on Monday 21 September 2026. Interviews are expected to be held in November 2026.

Apply here https://my.corehr.com/pls/uoxrecruit/erq_jobspec_version_4.display_form

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