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)

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

• 10:00 – 10:15 Welcome and aims for the day (DSAIL)
• 10:15 – 11:15 Lightning talks (10–15 minutes each) + structured Q&A
• 11.15 - 11.30 Coffee break
• 11:30 – 12:30 Lightning talks (10–15 minutes each) + structured Q&A
• 12:30 – 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 for AI for Science Workshop
• Presentation submission now closed
• Poster: Indicate in your registration that you would like to bring a poster (and whether you need DSAIL to pay the printing charge)

2. Available Studentships & What They Cover

Each EPSRC DLA studentship provides:

• 3.5 years of Home tuition fees and stipend at the UKRI minimum rate.
• £1,000 per annum Research Training Support Grant (RTSG).

Up to 30% of the total EPSRC DLA studentships across the Faculty may be offered to Overseas candidates, subject to Faculty approval to ensure the overall cap is not exceeded. If you intend to target an Overseas student, please flag this clearly in your proposal.

3. EPSRC Remit and Eligibility

Projects must sit squarely within the EPSRC remit (Engineering & Physical Sciences). If your topic is borderline, you must justify the EPSRC alignment explicitly. Interdisciplinary proposals are encouraged, provided the core research questions and methods remain predominantly within EPSRC scope.

Supervisory teams must include at least one member of DSAIL. Cross-departmental teams are strongly encouraged. Early Career Researchers are encouraged to apply and may co-lead proposals with appropriate mentorship.

4. Collaborative Requirement (Doctoral Landscape Award)

EPSRC expects at least 25% of studentships funded through the DLA to include a substantive collaborative component. For this call, you are strongly encouraged to embed a collaboration from the outset. Collaboration is defined as:

Working with one or more external non-academic partners who take an active role in the direction and outputs of the doctoral project and provide cash and/or in-kind contributions.

There is no minimum monetary value stipulated, but proposals should articulate:

• The partner organisation(s) and their sector.
• Nature and scale of contributions (cash, data, staff time, facilities, placements, etc.).
• Planned mechanisms for steering/project governance (e.g. quarterly meetings, joint supervision).
• Expected mutual benefits and impact pathways.

If collaboration cannot be confirmed before submission, outline a credible plan and timeline to secure it during the studentship.

5. Proposal Requirements (MAXIMUM 3 PAGES)

Submissions must not exceed three A4 pages (minimum 11pt font, standard margins). A separate reference list (optional, max ½ page) will not count towards the limit.

Please structure your proposal using the following headings:

1. Project Title
2. Supervisory Team (names, departments/schools, roles; indicate ECR status where relevant)
3. EPSRC Remit & Fit (succinct justification)
4. Rationale & Objectives (key research questions, novelty, expected contributions)
5. Methodology & Data/Resources (core methods, datasets, infrastructure)
6. Collaboration Plan (partner(s), contributions, engagement model; or plan to secure)
7. Cross-Disciplinary Elements (how the work spans disciplines and why this matters)
8. Impact & Alignment with DSAIL/University Strategies
9. Student Development & Training (planned skills training, placements, cohort activities)
10. Equality, Diversity & Inclusion Considerations (brief statement on inclusive recruitment and supervision)

Optional: References (½ page max).

Submissions that fail to comply with the page limit or required headings may be returned without review.

6. Selection Criteria

Proposals will be assessed by a DSAIL panel (augmented as needed for domain expertise) using the following criteria:

1. Fit to EPSRC remit (pass/fail).
2. Quality and novelty of the research (scientific excellence, clarity of objectives).
3. Strength and credibility of the collaborative element (partner engagement, contributions, governance).
4. Cross-disciplinarity and alignment with DSAIL’s mission (breadth/ depth of disciplinary integration).
5. Feasibility and supervisory capacity (methods, resources, training environment, track record/mentorship plan).
6. Impact potential (academic, industrial/societal, REF alignment).
7. Student experience & development (training, placements, cohort activities).

Where proposals are otherwise equal, those demonstrating stronger cross-disciplinary reach and/or collaboration will be prioritised.

7. Submission Process

• Format: Single PDF, 3 pages (plus optional references).
• File name convention: DSAIL_DLA26_Surname_ShortTitle.pdf.
• How to submit: Email the PDF to dsail@lancaster.ac.uk with subject line: “DSAIL EPSRC DLA Proposal 2026 – [PI Surname]”.
• Deadline: 17:00 (BST), 16^th April 2026. Late submissions will not be considered without prior agreement.