We are working to create a world-class Data Science and AI @ Lancaster Institute (DSAIL) that sets the global standard for a truly interdisciplinary approach to contemporary data-driven research challenges. DSAIL 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 and AI 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 350 affiliated academics, researchers, and students.

Our data science, AI, 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.

What to expect

• Short, focused talks (10–15 minutes): Lightning-style presentations from academics, PDRAs and PhD students on how AI is enabling scientific research and discovery.
• What worked (and what didn’t): Each speaker will briefly cover (i) the core problem, (ii) the AI method(s) used, (iii) what was learned/achieved, and (iv) limitations—data issues, compute constraints, evaluation challenges, reproducibility, governance/ethics, etc.
• Poster + networking session (over lunch): A lively, informal opportunity to circulate, ask questions, and identify overlap across projects. Posters are strongly encouraged.
• Breakout discussions: Facilitated small-group sessions to identify shared needs (data, tools, compute, evaluation, governance), collaboration opportunities, and concrete next steps—particularly towards future external funding and cross-faculty initiatives.
• Practical takeaways: A curated set of themes, candidate collaborations, and an initial “opportunity map” for AI for Science activity at Lancaster.

Call for presenters (talks + posters)

We are actively seeking short talks (10–15 minutes) on any activity that fits “AI for Science” in the broadest sense. This includes methodological work, applied case studies, infrastructure/tooling, or evaluation and governance approaches that enable scientific progress.

Examples of suitable topics include (not limited to):

• AI for scientific discovery (new hypotheses, new materials, new mechanisms, new insights)
• AI for simulation and scientific computing (surrogates, emulators, PDE learning, accelerators)
• AI for experiments and measurement (automation, control, adaptive/active learning, lab/field workflows)
• AI for data assimilation and inverse problems (uncertainty quantification, calibration, causal inference)
• AI for earth and environmental science, climate, ecology, biodiversity, geoscience
• AI for health, medicine, life sciences, imaging, genomics, epidemiology
• AI for engineering, energy systems, manufacturing, sensors, robotics
• AI for evaluation and robustness in scientific settings (ground truth scarcity, dataset shift, validation)
• Responsible and trustworthy AI for scientific practice (reproducibility, data governance, ethics)

Poster displays: If you have a poster we will provide space for displays and discussion during the lunch session. We can also cover the cost of printing the poster.

Who should attend

• Academic staff and researchers working in, or curious about, AI-enabled science
• PDRAs and PhD students with AI-for-science methods or applications
• Research software engineers, data specialists, lab/technical teams, and professional services colleagues supporting research
• Anyone interested in building cross-disciplinary collaborations around scientific AI

Provisional schedule (10:00 AM – 3:00 PM)

• 10:00 – 10:15 Welcome and aims for the day (DSAIL)
• 10:15 – 10:45 Framing session: “What counts as AI for Science?” (shared language, examples, evaluation expectations)
• 10:45 – 12:15 Lightning talks (10–15 minutes each) + structured Q&A
• 12:15 – 1:15 Lunch + poster session + networking
• 1:15 – 2:15 Breakout sessions (theme-led groups; capture opportunities and blockers)
• 2:15 – 2:45 Report-back from groups (short summaries, candidate collaborations)
• 2:45 – 3:00 Close: Wrap-up and next steps.

Light refreshments will be available throughout the day. Lunch will also be provided, please indicate dietary requirements via the Eventbrite registration.

How to get involved

• Attend: Register here
• Present: Submit a proposed title + 2–4 sentence summary with your registration
• Poster: Indicate in your registration that you would like to bring a poster (and whether you need DSAIL to pay the printing charge)

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 cyber security 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 Cyber security 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)
• Professor 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) a First or Upper Second-Class degree (or equivalent) in Computer Science, Data Science, or Cyber security. 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, cyber security, computer networking and AI tooling. However, candidates should be aware that this PhD will have a substantial cyber security 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 Professor Nicholas Race (n.race@lancaster.ac.uk) and Dr Edward Austin (e.austin@lancaster.ac.uk)

Coffee chats run monthly on the last Monday of each month in the Sky Lounge or the LEC atrium. Coffee and biscuits will be provided—please remember to bring your own mug.

Come along to connect, collaborate, and enjoy a coffee or tea while helping to shape the future of interdisciplinary environmental research at Lancaster.

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