Apply now for a place on the prestigious Alan Turing Institute PhD Enrichment Scheme at the Jean Golding Institute at the University of Bristol
Turing PhD Enrichment Scheme
The University of Bristol is one of only two UK universities that have been selected to deliver the Turing’s PhD Enrichment Scheme. The first cohort of Turing Bristol enrichment students will start in autumn 2021.
This is an opportunity for UK PhD students to spend up to 12 months at the University of Bristol and be part of Bristol’s vibrant and artistic atmosphere while developing research collaborations. The University of Bristol consistently ranks in the UK's top ten universities in league tables on both research and teaching excellence.
Why choose Bristol?
The Enrichment scheme at Bristol will provide you with an opportunity to collaborate with top data scientists, the University of Bristol has the highest number of Centres for Doctoral Training (EPSRC CDTs) in fields related data science and AI in the UK, including the Computational Statistics and Data Science CDT (COMPASS) and the Interactive Artificial Intelligence CDT. Successful applicants will have the opportunity to connect with these groups and join a cohort of enrichment students from across the UK that aims to develop interdisciplinary network across the Turing data science community.
Who can apply?
Applications from a broad range of academic disciplines are encouraged. As well as maintaining usual contact with your home university supervisor, during your placement you will be supervised by University academics, some of them are also Turing Fellows, with whom you will collaborate on your enrichment project.
Full details of how to apply can be found on the Alan Turing Institute website. We strongly recommend your read all the guidance before applying, including the FAQs.
Closing date 2 February, 12pm (noon) GMT.
You might like to contact one of the academics listed below to have an initial discussion about your ideas for a collaborative project. But please note that this does not guarantee you a place on the scheme.
Computational modelling of complex materials and biological applications
Bristol Turing Fellow and Director of the Jean Golding Institute, Professor Kate Robson Brown's research explores the microstructure of living tissues and their response to changing and extreme environments; innovating methodologies for the capture, computational modelling, analysis and interpretation of data describing complex material and structural characterisation. Bioscience applications of these methods include forensic science and pathology, the regulation of hard tissue growth and development, and the study of biomechanical systems. Engineering applications include employing the ontogeny of tissue microstructure as a model of programmed transformation in 4D materials, biomimetics in engineering design, and multi-scale modelling of complex hierarchical structures and systems.
Computational and mathematical neuroscience
Turing Fellow Conor Houghton is an Associate Professor in Mathematical Neuroscience. His research interest is in understanding information processing and coding in the brain.
Anticipation and Cyber Risk
Genevieve Liveley, Associate Professor in Classics, RISCS Fellow, and Turing Fellow has research interests in ancient narratives and in narrative theories (both ancient and modern), and their impact on futures thinking. She has published a number of books and articles on these topics and has also worked on the classical tradition, chaos theory, and cyborgs.
Turing Fellow, Professor William Browne’s research spans the area of statistical modelling, from the development of statistical methods to fit realistically complex statistical models to describe real-life problems, through the implementation of those models in statistical software to the application of the methods in several application areas.
Turing Fellow Dr Emmanouil Tranos is interested in the spatiality of the digital economy and has published on issues related to the geography of the internet infrastructure, the economic impacts that such digital infrastructure can generate on cities and regions and the position of cities within spatial, complex networks.
Turing Fellow Levi Wolf works on methods in statistics, data science, and machine learning for the analysis of social processes. In the past, he has worked on detecting gerrymandering, neighbourhood dynamics, local models, bayesian computation… a whole gamut of spatial data science topics.
Turing Fellow Sean Fox’s research focuses on urbanisation and urban development, particularly (but not exclusively) in Africa and Asia. He is interested in research that contributes to building a global urban science to support planning, policies and technologies geared towards ensuring a more sustainable urban future. Topics of interest include population structure and change, mobility, economic development, energy, inequality, and identifying new sources of data in rapidly changing cities.
Theory and algorithms
Professor Nick Whiteley is a Heilbronn Chair in Data Science, as well as a Turing Fellow.His research interests are: Statistical Inference in high-dimensional dynamic stochastic systems, Non-linear filtering theory and algorithms, Interface between convex optimization, probabilistic modelling and sampling method and Bayesian modelling, hidden Markov models, state-space models, time series.
Population Health Data Science
Turing Fellow Professor Andrew Dowsey's research is in applied data science and artificial intelligence for the health sciences within both human and animal domains. As part of our Health Data Research UK South-West Better Care Partnership his team are developing prediction models across linked patient records and lab results of millions of people for better antibiotic prescribing that tackles the threat of antimicrobial resistance. He also works to provide better biomarker discovery from biological samples through the analysis of large-scale proteomics and metabolomics data, and develops computer vision and deep learning approaches to animal monitoring for early detection of disease and welfare issues.
Turing Fellow, Professor Tom Gaunt and his research team at the MRC Integrative Epidemiology Unit work on the application of AI, data integration and data mining to build and interrogate biomedical knowledge graphs. His work is motivated by the need to find new systematic ways to investigate the aetiology of common diseases and identify/prioritise potential intervention targets.
Digital Innovation and Well-being
Turing Fellow Anya Skatova has recently been awarded a very prestigious Future Leader Fellowship. Her main area of interest is understanding of how novel digital footprint data can be used to study human behaviour and real-life outcomes, such as health. Currently she is focusing on transaction data, specifically loyalty and banking cards, and working on realising the value of using these data to improve population health.
Cellular and molecular data to study heart disease using Cryo EM
Turing Fellow Danielle Paul, also a British Hearth Foundation Research Fellow, is currently researching Cryo Electron Microscopy of cardiac thin filaments: the molecular basis of heart disease.