About us

We are working to create a world-class Data Science Institute at Lancaster (DSI@Lancaster) that sets the global standard for a truly interdisciplinary approach to contemporary data-driven research challenges. DSI@Lancaster aims to have an internationally recognised and distinctive strength in being able to provide an end-to-end interdisciplinary research capability - from infrastructure and fundamentals through to globally relevant problem domains and the social, legal and ethical issues raised by the use of Data Science.

The Institute is initially focusing on the fundamentals of Data Science including security and privacy together with cross-cutting theme areas consisting of environment, resilience and sustainability;health and ageing, data and society and creating a world-leading institute with over 300 affiliated academics, researchers, and students.

Our data science, health data science and business analytics programmes have launched the careers of hundreds of data professionals over the last 10 years. Students from our programmes have progressed to data science roles at Amazon, PWC, Ernst & Young, Hawaiian Airlines, eBay, Zurich Insurance, the Co-operative Group, N Brown, the NHS and many others - please look at our Education pages for further details of the courses on offer.

ExaGEO, a partnership between Lancaster University (CEEDS), the University of Glasgow, and the University of Edinburgh (EPCC), offers fully funded PhDs in geo- and computer sciences, statistics, and computational engineering. ExaGEO will deliver the next generation of Earth and environmental scientists trained in exascale computing techniques. We do this through a holistic and multidisciplinary program targeting excellence in both the technical (graphical processing unit, GPU) skills required for the development and application of software and multidisciplinary ‘domain’ training in the complexity of simulated Earth system processes.

Benefits of the Programme

• A fully funded PhD project (3.5 years) supported by a Research Training Support Grant;
• Research and professional skills training, outreach events, summer schools and workshops;
• Internship and placement opportunities;
• A supervisory team consisting of multidisciplinary supervisors;
• The choice of undertaking your PhD at any of our partner institutions;
• Research and training opportunities in state-of-the-art GPU programming and modelling techniques intended for exascale computing applications;
• Opportunities for PhD research topics across a diverse range of Earth and environmental science disciplines.

Funding and Eligibility

Funding covers tuition fees for UK home applicants, as well as an annual stipend at the standard UKRI rate (currently £19,237). To be classed as a home applicant, candidates must meet the following criteria:

• Be a UK national or UK/EU dual national or non-UK national with settled status / pre-settled status / indefinite leave to remain / indefinite leave to enter / discretionary leave / EU migrant worker in the UK or non-UK national with a claim for asylum or the family member of such a person, and
• Have ordinary residence in the UK, Channel Islands, Isle of Man or British Overseas Territory, at the Point of Application, and
• Have three years residency in the UK, Channel Islands, Isle of Man, British Overseas Territory or EEA before the relevant date of application unless residency outside of the UK/ EEA has been of a temporary nature only and of a period less than six years.

There are a limited number of international studentships available for exceptional candidates who do not meet the UK home studentship status eligibility requirements. Funding for successful international students will match that of home students and no international top-up fees will be payable.

Applicants must have, or expect to obtain, the equivalent of a 1st or 2:1 degree in a relevant subject, e.g., chemistry, computing science, earth/geo/environmental sciences, engineering, geography, mathematics etc.

Equality, Diversity and Inclusion

ExaGEO, and our partner institutions, champion EDI, believing that this is the way to increase research productivity and quality and to enhance societal and economic impact.

How to Apply

Applications must be submitted through the University of Glasgow’s online application system, regardless of where the PhD will be based.

Contact Us

exageo-info@glasgow.ac.uk

PhD Overview

As society becomes increasingly reliant on digital infrastructure, it is critical that decision-makers at organisational and national levels understand the resilience of their systems. Analysts use Attack Surface Mapping (ASM) to identify their internet-connected digital assets and associated vulnerabilities. This allows them to understand how robust the infrastructure is, plan mitigation strategies, and support recovery post-attack.

This PhD will leverage data-science, AI, and cybersecurity techniques to develop the next generation of ASM tools. Research will include:

• Fusing multiple ASM tools and pieces of open-source information to give more accurate understanding of attack surfaces than the current state-of-the-art tools can provide.
• Developing techniques to measure and interpret the uncertainty of ASM results, giving practitioners confidence in their analysis.
• Investigating how AI automation can safely and effectively improve the ASM process.

This PhD is in collaboration with SP Electricity North West, with a crucial focus on securing digital infrastructure across their network and enabling the secure deployment of innovative new services as they digitise their operations. Furthermore, this project aligns with ongoing work the team are carrying out with the UK’s National Cybersecurity Centre (NCSC); as such, there is a real opportunity for your research to make an impact.

Supervisory Team

• Dr Edward Austin(School of Computing and Communications)
• Prof Nicholas Race(School of Computing and Communications)
• Dr Xiandong Ma (School of Engineering)

Training and Development

The successful candidate will receive a tailored training programme including:

• Support using, and access to, ASM tools such as Shodan and Censys.
• Opportunities to engage with national and international conferences, workshops, and training events.
• Insight into the power sector through industrial collaboration with SP ENWL.

Funding

• A 3.5-year UKRI-funded studentship, including a stipend (currently £20,780 per year) and full tuition fees for Home students.
• An additional research training grant (£1,000 per year) for consumables, maintenance, and travel to events/conferences.

Eligibility

• Applicants should have (or expect to obtain) aFirst or Upper Second-Class degree (or equivalent) in Computer Science, Data Science, or Cybersecurity. Applicants from other disciplines with a substantial mathematical component are also encouraged to apply.
• There is no expectation that a candidate will be proficient in all areas of data science, cybersecurity, computer networking and AI tooling. However, candidates should be aware that this PhD will have a substantial cybersecurity component.

Application Process

Applicants should submit:

1. A cover letter outlining their motivation and suitability.
2. A CV outlining skills and experience.

Applications will be considered on a rolling basis until the position is filled. The expected start dates are either April 2026 or October 2026.

Contact Information

Please contact Prof Nicholas Race (n.race@lancaster.ac.uk) & Dr Edward Austin (e.austin@lancaster.ac.uk)

Questions? Contact Julia Carradus j.carradus1@lancaster.ac.uk