Data Science and AI Institute @ Lancaster

We aim to set the global standard for a truly interdisciplinary approach to contemporary data-driven research challenges. The Data Science and AI Institute @ Lancaster (DSAIL) has over 350 members and has raised £70 million in research grants.

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Data Science and AI @ Lancaster (DSAIL)

The Data Science Institute is preparing for an important next step. From January 2026, we will be updating our name to Data Science and AI @ Lancaster (DSAIL), reflecting more clearly the Institute’s growing role as a focal point for artificial intelligence research, education and engagement across the University and beyond. You will see this new identity rolling out across our communications, events and online presence in the new year, but the core mission remains the same: to support and connect Lancaster’s data science and AI community.

Data Science and AI at Lancaster builds on the University’s longstanding strengths in computational and data-driven research. This environment is enriched by a broad interdisciplinary community of researchers working across fields including environmental science, health and medicine, sociology and the creative arts. Through the Data Science and AI Institute @ Lancaster (DSAIL), Lancaster is creating a world-class institute that sets the global standard for a genuinely interdisciplinary approach to contemporary data-driven research challenges. The Institute focuses on the foundations of data science and artificial intelligence, alongside a number of cross-cutting thematic areas.

DSAIL@Lancaster aims to be internationally recognised for its distinctive end-to-end interdisciplinary research capability, spanning infrastructure and fundamentals, globally relevant application domains, and the social, legal and ethical questions raised by data science and AI. By connecting expertise across disciplines, the Institute provides a focal point for research, education and engagement in data science and artificial intelligence across the University and beyond.

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.

Latest News & Grant Opportunities

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DSAIL Workshop Call 2026/27 is offering funding of up to £5,000 per workshop for interdisciplinary research workshops

DSAIL is offering funding of up to £5,000 per workshop for interdisciplinary research workshops to be held at Lancaster before the end of the 2026/27 academic year. The purpose of this funding is to seed new collaborations across disciplines, build communities around emerging areas of data science and AI, and lay the groundwork for future joint research projects and funding bids. Our only stipulation is that workshops must demonstrate collaboration beyond a single discipline.

Please note that £5,000 is an upper limit, and we encourage applicants to think carefully about their budget requests so that as many workshops as possible can be supported. DSAIL funds can be combined with other sources of funding to expand the scope and reach of a workshop, and preference will be given to proposals from early career staff.

Deadline: Friday 30th October 2026. Proposals (max. two sides of A4) should be sent to dsail@lancaster.ac.uk. Successful applicants will be informed during the week commencing 16th November.

The Data Science and AI Institute at Lancaster (DSAIL) invites nominations for three prizes

The Data Science and AI Institute at Lancaster (DSAIL) invites nominations for three prizes celebrating excellence and inclusive impact across data science and AI. We particularly welcome applications from individuals from historically underrepresented and underserved backgrounds, and we will make adjustments for career breaks.

Who can nominate: Self-nominations and nominations by others are equally welcome. For those in leadership roles, please encourage and support others to apply.

Eligibility (all prizes): Nominees must be current members of DSAIL. Further eligibility criteria for individual prizes are set out below.

Award for each prize: Certificate + Gift voucher (one prize per category).

Inclusive Selection Process: Applications from individuals from underrepresented and underserved backgrounds are particularly encouraged, and special consideration will be given to applicants who have faced systemic barriers in academia. Additional time will be allowed for career breaks. A wide variety of reasons will be recognised. For parental leave, we allow 18 months per child for birthing parents, 6 months per child for non-birthing parents by default, but please state if a longer duration is required.

Submissions details:

  • Closing date:17:00, Friday 27 November 2026
  • What to include: 1 x Statement explaining how the nominee addresses the criteria for the award (max 2 pages)
  • (Optional):Provide any further details relevant to your application. This section is optional and can be up to 200 words. You should not use it to describe additional skills, experiences, or outputs, but you can use it to describe any factors that provide context for the rest of your application (for example, details of career breaks if you wish to disclose them).
  • Submitting: Documents to be emailed to:dsail@lancaster.ac.uk
  • Announcement of winners: Prizes will be announced at the Pies and Prizes event on Monday 14 December 2026
  1. Early Career Researcher Award

This award recognises exceptional academic contributions to data science and AI by researchers who are in the early stages of their careers.

Eligibility:

  • Researchers within 5 years of completing their PhD (or equivalent).
  • Current member of DSAIL.
  • Actively engaged in academic research in data science, AI, or related fields.

Assessment Criteria:

  • Research Innovation: Demonstrated contributions to innovative, high-impact research in data science or AI.
  • Mentorship and Collaboration: Active engagement with the data science and AI community (formal or informal), including advocacy that creates opportunities for researchers and support for underrepresented groups.
  • Potential for Growth: Clear potential to make lasting, positive contributions to the academic community.

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  1. Diversity in Data Science Champion Award

This award celebrates academic researchers, faculty, or research teams who have made outstanding contributions to diversity, equity, and inclusion within data science and AI, with a focus on creating pathways for historically underrepresented and underserved groups.

Eligibility:

  • Open to researchers, faculty, or teams who are current members of DSAIL.
  • We are looking for individuals or teams that embed diversity, inclusion, and equity in their academic work and/or actively foster these values within their team and beyond through community engagement.

We note the potential diversity of contributions. Applications should address at least one of the following, as relevant to your specific contribution.

Indicative Assessment Criteria:

  • Leadership in Inclusivity: Demonstrated efforts to create inclusive academic spaces for historically underrepresented or underserved groups in data science and AI.
  • Institutional Change: Evidence of driving institutional or structural change that supports diversity, equity, and inclusion.
  • Mentorship & Advocacy: Active involvement in mentorship or advocacy programs that support underrepresented or underserved students and early-career researchers in data science or AI.
  • Community Engagement: Efforts to collaborate with or serve underrepresented communities within or outside of academia.

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  1. Outstanding Contribution to Data Science & AI

This open-category award recognises individuals who have made outstanding contributions of any kind to the data science and AI community at Lancaster. Contributions may include, but are not limited to, excellence in teaching, research, research impact, and engagement.

Eligibility:

  • Open to all current members of DSAIL, at any career stage.

Contributions to the community take many forms. Nominations should address at least one of the following, as relevant to the specific contribution.

Indicative Assessment Criteria:

  • Teaching & Education: Excellence in teaching, supervision, or curriculum development in data science and AI, including inclusive educational practice and fostering diverse talent.
  • Research Excellence: High-quality, innovative research in data science or AI that has advanced the field.
  • Research Impact: Evidence that research has made a difference beyond academia, for example in industry, policy, health, the environment, or wider society.
  • Engagement & Community: Contributions that strengthen the data science and AI community at Lancaster and beyond, for example public engagement and outreach, organising events, seminars or training, mentoring colleagues, or supporting underrepresented groups.

Call for Applications: Gender Diversity in Data Science & AI Grant

Data Science and AI @ Lancaster (DSAIL) is delighted to announce a 2026 call for applications to the Gender Diversity in Data Science and AI Grant.

This grant supports the research activities of women and other marginalised genders (including non-binary and gender-diverse individuals) in the fields of data science and AI. Women are significantly underrepresented in this area, with only 22% of data science professionals being women (Wajcman et al, 2024, Turing Institute Report). This grant aims to address gender disparities and improve retention of women and marginalised gender researchers by providing financial support for research, career development, and increased visibility in the field. Apply now to help build a more inclusive future in data science.

The application form and full criteria can be found below (downloadable form will be added shortly)

Eligibility and scope

  • Open to DSAIL members who identify as women or marginalised gender researchers at any career stage in data science or AI research.
  • This funding opportunity aims to support an individual’s research expenses, conference travel, professional development, and/or related activities.
  • Up to three applications will be awarded in this round.
  • Activities supported through the award must be completed, with all associated spending completed by July 31st

Application details

  • Submit a completed application form and 2-page CV (form and CV template below).
  • Deadline: 15:00, 13 Nov 2026. Late submissions will not be accepted.
  • Maximum request for individual applications should not exceed £1500; costs should be clearly explained and justified.
  • Total award amount across applications: £3000.
  • Send your application to carradus1@lancaster.ac.uk with the subject heading “Gender Diversity in Data Science Grant Proposal”.
  • Please contact carradus1@lancaster.ac.uk if you have any questions about the scheme, who will refer you to the most appropriate person.

Selection process

Applications will be reviewed by members drawn from the DSAIL Leadership team and the DSAIL Diversity in Data Science and AI Working Group. We aim to inform applicants of the outcome within one month of the submission date.

Assessment criteria

Need (30%; 250 words max.)
  • Clear explanation of barriers faced in pursuing data science and/or AI research.
  • How the funding will help overcome these challenges.
Impact (30%; 250 words max.)
  • How the award will support career growth or education in data science and/or AI.
  • Potential long-term benefits for the applicant.
Plan (20%; 100 words max.)
  • A clear, realistic explanation of how the funds will be used.
CV (20%; 2 pages)
  • Clear involvement in data science or AI research.
  • Evidence of wider impacts through academic engagement, teaching, mentorship, outreach or service.

Application: DSAIL Gender Diversity in Data Science and AI Grant 2026

Please send your application, along with a short CV (max. 2 pages using the template below), to j.carradus1@lancaster.ac.uk with the subject heading “Gender Diversity in Data Science Grant Proposal” by 15:00 Friday 13 Nov 2026.

CV Template (max. 2 pages)

Name:

  1. Education
  2. Research and Academic Appointments
  3. Top 5 Publications
  4. Grants, Awards, Honors
  5. Teaching and Mentorship
  6. Key Presentations, Conferences, Working Groups
  7. Outreach and Service

Call for Applications: Reducing Structural Bias in Data Science & AI Grant

Data Science and AI @ Lancaster (DSAIL) is delighted to announce a 2026 call for applications to the Reducing Structural Bias in Data Science & AI Grant.

This grant supports research, engagement, and innovation that confronts structural bias in AI and data science, particularly the kinds of bias that negatively impact underrepresented groups. Despite the transformative potential of AI and data-driven technologies, these systems often reflect and reinforce the biases embedded in the data, methods, and structures that produce them, and in their anticipated usage and users. AI models are often based on data volunteered by specific sections of society, as opposed to carefully designed scientific studies. This means that AI results might be less appropriate for, or even harmful to, underrepresented or marginalised groups.

This funding opportunity seeks to support researchers and practitioners working to tackle these challenges head-on.

The application form and criteria can be found below (downloadable form to be added)

ELIGIBILITY & SCOPE

  • Open to DSAIL members (click here to join) at any career stage across all disciplines.
  • This funding opportunity is intended to:
    • Support innovative research that identifies, measures, or mitigates structural bias towards underrepresented and/or underserved groups in data science, AI and adjacent disciplines.
    • Provide seed funding for early-stage projects with the potential to lead to larger-scale funding or institutional
    • Enable the development of responsible data science and AI strategies.
    • Foster interdisciplinary collaborations and community engagement that centre equity, inclusion, and justice in technical work.
  • Funds can be used for personnel, data acquisition, community engagement, workshop organisation, exploratory research, and other relevant activities.
  • Up to three applications will be awarded in this round.
  • Activities supported through the award must be completed, with all associated spending completed by 31st July 2027.

APPLICATION DETAILS

  • Submit a completed application form (form below).
  • Deadline: 15:00, Friday 13th Nov 2026. Late submissions will not be accepted.
  • Maximum request for individual applications should not exceed £2500; costs should be clearly explained and justified.
  • Total award amount across applications: £5000.
  • Send your application to carradus1@lancaster.ac.uk with the subject heading “Reducing Structural Bias in Data Science and AI Grant Proposal”.
  • Please contact carradus1@lancaster.ac.uk if you have any questions about the scheme, who will refer you to the most appropriate person.

SELECTION PROCESS

Applications will be reviewed by members drawn from the DSAIL Leadership team and the DSAIL Diversity in Data Science and AI Working Group. We aim to inform applicants of the outcome within one month of the submission date.

ASSESSMENT CRITERIA

  1. Vision and Fit (40%; 300 words max.)
  • Does the proposal offer novel ideas or approaches to address bias against underrepresented groups in AI and/or data science?
  • Does it align with the goals of fostering inclusivity, equity, and responsible innovation in data science?
  • Does the project have a clear path toward scale-up, continuation, or integration into a larger body of work?
  • Will the outcomes position the team to pursue additional funding?
  1. Approach (40%; 300 words max.)
  • Does the proposal include a clear plan for the activity (e.g. data collection, specification of appropriate analytical techniques, or identification of potential workshop speakers or partners for engagement activity)?
  • Is the timeline realistic given the scope of work and budget?
  • Is the budget appropriate and clearly justified?
  1. Team expertise (20%; 150 words max.)
  • Does the team have the necessary expertise to execute the project?
  • Are interdisciplinary or cross-sector collaborations included where relevant?
  • Does the team reflect or actively engage diverse perspectives?

Application: DSAIL Reducing Structural Bias in Data Science & AI Grant 2026

Please send your application to j.carradus1@lancaster.ac.uk with the subject heading “Reducing Structural Bias in Data Science & AI Grant Proposal” by 15:00 on Friday 13th Nov 2026. Please delete guidance provided in each box before submission.

  1. Vision and Fit (max. 300 words)

· Does the proposal offer novel ideas or approaches to identify or mitigate bias against underrepresented groups in AI and/or data science?

· Does it align with the goals of fostering inclusivity, equity, and responsible innovation in data science?

· Does the project have a clear path toward scale-up, continuation, or integration into a larger body of work?

· Will the outcomes position the team to pursue additional funding?
  1. Approach (max. 300 words)

· Does the proposal include clear, appropriate plans for data collection, analysis, and/or engagement?

· Is the timeline realistic given the scope of work and budget?

· Is the budget appropriate and clearly justified?
  1. Team Expertise (max. 150 words)

· Does the team have the necessary expertise to execute the project?

· Are interdisciplinary or cross-sector collaborations included where relevant?

· Does the team reflect or actively engage diverse perspectives?

DSAIL AI Showcase Event took place on Monday 28th September at Lancaster House Hotel

The Data Science and AI Institute at Lancaster (DSAIL) welcomed researchers, businesses and partners to Lancaster House Hotel on 28 September for a showcase event exploring how artificial intelligence is reshaping research, industry and society, and the responsibilities that come with it.

The event "Exploring Data. Shaping AI. Driving Impact." combined interactive sessions, research presentations and a panel discussion to demonstrate the breadth of data science and AI work happening across the University while opening up new conversations on collaboration and responsible AI.

Opening the day, Professor Chris Nemeth and Professor Nigel Davies, Co-Directors of DSAIL, shared the Institute's successes so far, including its growth into a community of 461 members across the University. Attendees heard that 2025/26 was a record year for the Institute, with £16.9m awarded across 31 grants, while its 35 events drew more than 900 attendees.

Can AI judge? A keynote on trust, funding and generative AI

The day's keynote, "Trust in the VoIDs: following the trail of £580,000 of public funds", was delivered by Professor Claire Hardaker, Professor of Linguistics at Lancaster University and DSAIL Integrity Theme Lead. The presentation explored what happens to trust and accountability when generative AI tools help decide who receives public funding. Professor Hardaker drew on her bid for funding into AI-generated voices, which was screened out at the AI assessment stage before reaching a human reviewer, to ask whether large language models could be relied on as reviewers.

Research across disciplines

The event reflected DSAIL's interdisciplinary approach and included a session on diversity in DSAIL, which introduced the Institute's diversity working group, whose aims are to reduce barriers and increase opportunities for underrepresented and underserved groups in data science and AI.

In sessions based on each of DSAIL's five research themes, attendees explored the fundamental methods behind data science and AI and how they affect people, organisations and the environment:

  • Health brought together Lancaster researchers and external speakers to present the latest AI and data science research addressing key health challenges.
  • Environment paired short talks from academics at Lancaster and the UK Centre for Ecology & Hydrology with contributions from the Joint Nature Conservation Committee, Natural England and the Royal Society of Wildlife Trusts on the challenges they face around data science and AI.
  • Foundations showcased the diversity of research under this theme, with Lancaster University colleagues presenting their work.
  • Integrity took the form of a "data deli", where attendees shared ideas from their own fields relating to this theme and explored possible future collaborations.
  • Creativity explored how the current technological wave is rewriting the rules of authorship and originality, and what it means to be creative. This session featured contributions and live demonstrations from artists, designers, practitioners and researchers.

Universities in the world of AI

A panel discussion on "The Role of Universities in the World of AI" explored the contribution universities can make as AI becomes further embedded in research, industry and society. With much of today's AI development led by large technology companies, panellists discussed how universities can bring a critical lens, work more closely with industry, and help students and staff use AI responsibly and productively. The conversation also touched on the environmental impact of AI and how governments might invest wisely in such a fast-moving field.

Chaired by Professor Nemeth, the panel brought together:

  • Susan Zappala, Joint Nature Conservation Committee
  • Vishnu Chandrabalan, Chief Clinical Information Officer, NHS Lancashire and South Cumbria and Lancaster University
  • Brian Green, Head of Innovation and Mobile Development, Lancaster University
  • Dr Beatrice Wohl, RKE Research Fellow, Creative Computing Institute, University of the Arts London
  • Joe Lindley, DSAIL Creativity Theme Lead and Senior Research Fellow, School of Arts, Lancaster University
  • Gail Collyer-Hoar, PhD Student, Computing and Communications, Lancaster University

Building connections beyond the University

Alongside the formal event programme, the Showcase created space for researchers to meet representatives from businesses and industry, opening conversations on shared challenges and potential collaborations around ethics, trust, policy, skills and the deployment of data driven technologies. Lunch, refreshment breaks and a closing networking session gave attendees time to build those connections.

The event also reinforced DSAIL's role in connecting Lancaster's data science and AI community with the wider organisations it works alongside, helping translate research into real world impact.

For more information on DSAIL: https://www.lancaster.ac.uk/data-science-and-artificial-intelligence/

About the Data Science and AI Institute @ Lancaster

The Data Science and AI Institute at Lancaster (DSAIL) brings together Lancaster University's interdisciplinary strengths in data science and artificial intelligence. Through its research, teaching and partnerships, DSAIL aims to connect people working on data and AI across the University, and to work with businesses and other organisations to develop these technologies in ways that are responsible and beneficial.

  • Registration

  • Welcome

  • Theme session

  • Networking

Events

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The Unix Shell - an introduction to Linux and the Command Line - 13th October from 10am - 4.15

Carpentries this Autumn

Title: The Unix Shell - an introduction to Linux and the Command Line.

Room: SAT - Science & Technology PC Lab A008

Date: Tuesday, 13/10/2026

Carpentries this Autumn Tickets, Tuesday, October 13 • 10 AM - 4:15 PM | Eventbrite

The event itself will run from 10am - 4:15pm. Lunch is included

A day-long in-person course introducing the unix shell and working at the command line on Mac and Linux systems. Participants will learn how to navigate filesystems, run commands, process text files and make simple shell scripts.

Please let us know any dietary requirements

This is aimed at users with limited or no experience using the unix shell, in particular those who are planning to access Lancaster University's High-End Computing (HEC) or other compute clusters,

The course will be hands-on and will use either the Ubuntu Lab VDI instance at https://mylab.lancaster.ac.uk/ or the participant's own laptop. Participants will need to be either staff or a research student at Lancaster University.

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Introduction to High-Performance Computing on the HEC - 20th October at 10am - 4.15

Carpentries this Autumn

Title: Introduction to High-Performance Computing on the HEC

Room: FYL - Fylde D31Date: Tuesday, 20/10/2026

Carpentries this Autumn Tickets, Tuesday, October 20 • 10 AM - 4:15 PM | Eventbrite

The event itself will run from 10am - 4:15pm. Lunch included

Please let us know any dietary requirements

A day-long course introducing the basics of logging in, scheduling jobs, and managing research data using the High-End Computing (HEC) cluster. Participants will need to be either staff or a research student at Lancaster University; bring their own laptop; and be comfortable working on the Unix shell. The preceding course on Bash and the Unix shell is recommended for users who are new to both.

Check out this website too https://muse-writes.github.io/hpc-intro-hec/

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From Idea to grant proposal: a two part workshop for ECRs

From idea to grant proposal: a two-part workshop for ECRs

Do you have an idea for a research project but aren’t sure how to turn it into a grant proposal? We’re organising a 2-day workshop for early career researchers in environmental and data science to explore that process together.

Part 1 of 2: Developing your idea

14 October, 9.30 am–5 pm | Lancaster Castle

We’ll spend the day at Lancaster Castle, away from our usual workspaces, to make room for creative thinking. Facilitated by Dee Hennessy, this session will help you generate project ideas, form groups and develop a promising idea into the beginnings of a grant proposal. You’re welcome to bring an idea you already have, but you don’t need one to take part. At the end of the day, senior academics from CEEDS and DSAIL will join us online to offer feedback on the ideas in an academic research context.

To register follow this link: From idea to grant proposal: a two part workshop for ECRs – Fill in form

Places are limited to 21 and will be assigned on a first come first serve basis. So sign up soon to avoid disappointment!

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person sat in environment landscape with laptop

From Idea to grant proposal: a two part workshop for ECRs

Part 2 of 2: Turning your idea into a proposal

16 November, 9.30 am–5 pm | Health & Innovation Campus

The second workshop will focus on the practical steps of writing a grant proposal. You’ll work with the ideas developed on the first day and learn from experienced colleagues, including senior academics and research development staff, about shaping and presenting a compelling application.

Both days will be hands-on, with opportunities to work with other ECRs and ask questions. The workshop is particularly aimed at those who are new to the grant-writing experience, so no previous experience is required.

As this is a 2-part event priority will be given to those who sign up for both events. To register follow this link: From idea to grant proposal: a two part workshop for ECRs – Fill in form

Research Themes

Data Science at Lancaster was founded in 2015 on Lancaster’s historic research strengths in Computer Science, Statistics and Operational Research. The environment is further enriched by a broad community of data-driven researchers in a variety of other disciplines including the environmental sciences, health and medicine, sociology and the creative arts.

  • Creativity

    The Creativity theme researches how generative AI is transforming creative processes and reshaping notions of authorship and ownership, while also working to enable transdisciplinary inquiry through the use of creative methods to push the boundaries of data science and AI research.

  • Environment

    The Environment theme aims to develop new understanding and innovative solutions to the dual crises of climate change and biodiversity loss, which are inextricably linked. This time-critical mission requires close cross-disciplinary collaboration between ecologists, environmental scientists, computer sciences, statisticians, social scientists, and many others.

  • Foundations

    The Foundations theme covers the three main areas of data science, operational research, computer science and statistics. It blends the skills of researchers in these areas, to address challenges arising from industry and research.

  • Health

    The Health theme covers several areas of health, data science and AI from across the university, including biomedical, digital health technologies, health economics, medical imaging and health-related security, among many other areas.

  • Integrity

    The Integrity theme explores how societies can build trust, transparency, justice, fairness, accountability, and resilience in an era where AI and data-driven technologies evolve faster than the ethical processes, governance structures, and safeguarding interventions meant to oversee them.

Upcoming Events

5th Jan

Prob_AI Hub Winter School 2027

Tuesday 5 January 2027, 11:00am to Friday 8 January 2027, 1:00pm

More Events

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Call for technology providers to take action on AI non-consensual ‘deepfake pornography’

30 September 2026

For the first time, researchers have identified and named the key players facilitating the growing problem of AI-generated explicit sexual imagery online.
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Data Science and AI take centre stage at Lancaster University showcase

30 September 2026

The Data Science and AI Institute at Lancaster welcomed researchers, businesses and partners for a showcase event exploring how artificial intelligence is reshaping research, industry and society.
Cyber Security in the Nuclear Industry course - 2026 cohort

Cyber Security in the Nuclear Industry: Building a Resilient, Competent Workforce

16 September 2026

Lancaster University hosted professionals from across the nuclear sector for the sixth Cyber Security in the Nuclear Industry in-person training course, delivered in partnership with the World Institute for Nuclear Security (WINS) and the Austrian Institute of Technology (AIT).
Headache is one of the most common reasons people attend emergency departments

Why most emergency headache patients disappear into the data

15 September 2026

Thousands of people attend A&E with headaches every year but research suggests the way these visits are recorded may be hiding important clues about the needs of patients.
The Mindgard team

Major funding boost for Lancaster AI spin-out company

3 September 2026

A world-class technology spinout company from Lancaster University has raised US$30m (£22.2m) in a Series A funding round as demand intensifies around AI cyber security.

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