Events and opportunities

Check this page for the latest events and opportunities from around the Turing and organised by the Turing Liaison team.

Organised by the Turing Liaison team

Web Archives for Social Sciences Datathon

On 27–28 November 2025 we are organising a Web Archives for Social Sciences Datathon at the University of Bristol. This is in collaboration with our partners: the Common Crawl and UK Web Archive at The British Library. The datathon will take place at the BDFI Neutral Lab.

This two-day event will build capacity in the social science research community to use large-scale Web Archive data for policy-relevant, socio-economic research. Participants will work in teams with curated data extracts from the Common Crawl to address real-world research challenges. They will be supported by our expert facilitators.

Who should apply?

  • Early-career and more established researchers in the social sciences who currently use, or wish to use, web data for their research–especially data from Web Archives.
  • Researchers with technical backgrounds (e.g. data science) who want to apply their skills to Web Archive data for policy-relevant research.
  • Some prior experience with code-based tools (e.g. Python or R) is expected.

What will you gain?

By the end of the Datathon, you will be:

  • More confident in using Web Archives to address your own research questions.
  • Familiar with the structure, challenges, and opportunities of these data.
  • Equipped with technical expertise for working with Web Archive data at scale.
  • Experienced in using LLM for analysing such web data.

Practical details

When: 27–28 November 2025

Where: Bristol, BDFI Neutral Lab

Support: Limited financial assistance for travel and/or accommodation is available.

How to apply

Send a one-page document to Emmanouil Tranos (e.tranos@bristol.ac.uk) by 15 October 2025, including:

  • Your current position
  • Your research interests, particularly how you are using (or plan to use) Web Archive data
  • Your technical skills
  • Your location and whether you require financial support.

This Datathon is part of the Atlas of Econonic Activities project and is funded by SDR UK.

From around the Turing

  • AI+ Research Seminars, October – December 2025, King's College London, 15 October 2025 - 03 December 2025, 14:00 - 15:00
    • Hear directly from leading experts at King's College London about advancing AI research across diverse fields, from race and technology to computational biology to public health data. These monthly seminars showcase innovative approaches spanning disciplinary boundaries.
    • Listen to expert speakers:
      • 15 October - Dr Nessa Keddo on race and AI-generated content
      • 19 November - Dr Francisco Martin-Martinez on computational modelling of nature-inspired sustainable materials
      • 3 December - Dr Georgia Richards on harnessing open data to track preventable death.
    • All seminars are online, free to attend, and open to everyone interested in hearing more from the experts about how they are doing research in, for, and with AI at King's. 
    • Find out more here.
  • Turing Connections PhD Student Presentations and Networking Day, University College London, 24 October 2025, 10:00–17:00
    • Via the Turing Connections initiative, The Alan Turing Institute creates and signposts opportunities which are relevant to PhD students connected with data science and artificial intelligence.
    • These presentation and networking events are designed for PhD students to expand their network and build collaborations by meeting other Data Science and AI students, sharing research and improve communication and presentation skills.
    • The event is free, and the registration deadline is Wednesday 15 October 2025, 23:59
  • Present at the Oxford Digital Humanities Conference: 18 November 2025, University of Oxford
    • Audience: Graduate students and early career researchers
    • The conference is seeking to bring together researchers using computational methods in the humanities and languages fields across the UK. It will capture a wide range of subject areas across the many communities of scholars utilising digital methods - both from novices and expert practitioners.
    • Find out more about the Digital Humanities Conference
  • In-Person Networking Event: BridgeAI Adopters and Developers
    • 13 November 2025, 09:00 - 17:30
    • Venue: Wallacespace, London 
    • Exclusive in-person networking event designed to unite AI adopters, developers, and experts to accelerate innovation and responsible AI adoption across UK sectors
    • Hosted by The Alan Turing Institute, this event offers a unique opportunity to connect with SMEs from across the BridgeAI ecosystem.
    • Read more here
  • Simple Foundation Models for Astronomy: an Example Case with Lux
    • University of Liverpool, 11 November 2025, 15:00 - 16:00
    • Thanks to the efforts of large international collaborations there has been, and will continue to be, an unprecedented amount of data collected with telescopes from the ground or in space. These data are predominantly public, come in many different flavours, and are obtained for all types of astronomical objects (e.g., stars, galaxies, black holes...), enabling astronomers to chart from the smallest to the largest scales of the Cosmos.
    • However, while this deluge of data will provide all the necessary information to test current astrophysical theories and push our understanding of the formation of the Universe, we are yet to establish a sound-proof way of synergising all this high-dimensional, multi-modal, vast information.
    • Register here.
  • Machine Learning for Tuning and Control in Particle Accelerators
    • University of Liverpool, 09 December 2025, 15:00 - 16:00
    • Machine learning (ML) is a key technology for advancing particle accelerators and should play a central role in their future design. ML methods provide fast predictions at lower computational cost than analytical or classical numerical approaches, capture nonlinear correlations in data, and adapt to changes in machine conditions.
    • These capabilities enable robust online detection, prediction, optimisation, and control, while also supporting accelerator design by reducing the cost of numerical simulations and guiding parameter searches in high-dimensional spaces. Among ML applications, optimisation is particularly prominent, with Bayesian optimisation and reinforcement learning emerging as leading paradigms.
    • In this seminar, the speaker will focus on tuning and control tasks in particle accelerators using these methods and demonstrate their performance in real machines.
    • Register here.
  • Data Study Group January 2026: Save the date! 26 January - 06 February 2026
    • Audience: PhD students, post docs & early career researchers
    • Data Study Groups are intensive five-day collaborative, sprint-style research activities which bring together organisations from industry, government, and the third sector, with talented multi-disciplinary researchers from academia, to work on real-world problems.
    • January’s challenge will explore supply-demand gaps and trends in recruitment for AI roles across the UK labour market.
    • Find out more here: Data Study Group - January 2026 | The Alan Turing Institute
  • Artificially Intelligent BioSpatial Modeling: Decoding Tumor Geography
    • 27 October 2025, 15:00 - 16:00
    • This event will be held in hybrid form - you can join in the Enigma room at Floor 1 of the Alan Turing Institute
    • Part of the The Turing-Roche knowledge share series. 
    • The tumor microenvironment (TME) is increasingly recognized as a critical frontier in cancer research, revealing how the spatial organization and dynamic interactions among diverse cell populations govern immune responses, tumor progression, and therapeutic outcomes.
    • Veera Baladandayuthapani, Jeremy M.G. Taylor Collegiate Professor and Chair in the Department of Biostatistics at University of Michigan (UM), will discuss his perspective on how the conflation of AI techniques and biologically-informed rigorous statistical modeling can address these challenges and unlock actionable biological insights.
    • Find out more here.
  • Turing-Roche Knowledge Share Series - Artificially Intelligent BioSpatial Modeling: Decoding Tumor Geography
    • 27 October 2025, 15:00 - 16:00
    • Organised as part of The Turing-Roche knowledge share series, this month we will be hearing from Veera Baladandayuthapani, Jeremy M.G. Taylor Collegiate Professor and Chair in the Department of Biostatistics at University of Michigan (UM), where he also serves as the Associate Director of Quantitative Data Sciences and Director of the Cancer Data Science Shared Resource at UM Rogel Cancer Center.
    • Dr Baladandayuthapani will discuss frameworks for modelling spatially varying genomic networks and transcriptional programs, approaches for quantifying intercellular interactions within the TME, and strategies for linking spatial features to patient-specific clinical outcomes. The utility and translational potential of these methods will be illustrated through multiple case studies spanning diverse cancer types.
    • Find out more here.
  • Phi-ML meets Engineering - Machine learning dissipative dynamics via Statistical-Physics-Informed Neural Networks
    • 30 October 2025, 13:00 - 14:00
    • Part of the Phi-ML meets Engineering seminar series, exploring real-world applications of physics-informed machine learning (Φ-ML) methods to the engineering practice. They cover a wide range of topics, offering a cross-sectional view of the state of the art on Φ-ML research, worldwide.
    • Many physical systems can be described as a gradient flow (that is, a functional such as the entropy follows a steepest descent). In this talk, we address the problem of deriving such macroscopic (continuum) equations from microscopic (particle) data. The approach is physics-inspired, as the thermodynamic evolution of the entropy plays a central role. It will be shown that the 'thermodynamic' evolution operator can in various situations be learned from particle data via a fluctuation-dissipation result. Methodologically, as will be explained in the talk, this uses the 'stochastic version' of gradient flows, namely equation of fluctuating hydrodynamics.
    • Find out more here.

From Turing Interest Groups

Please join the groups via the links below to be sent more information and joining instructions for events.

  • Computing Life Interest Group Seminar 4

    • SPEAKER: Prof. Robert Insall (University College London)
    • WHEN/WHERE: Thursday 16, 14:00–15:00 BST - Zoom
    • TALK SUMMARY: How do immune cells find the right place?  Computational modelling of cell migration and chemotaxis
    • Join here
  • Causal Inference Interest Group: Making Rigorous Causal Inference More Mainstream
    • SPEAKER: Julia Rohrer (Wilhelm Wundt Institute for Psychology, Leipzig University)
    • WHEN/WHERE: 20-Oct-2025 3pm UK time (Zoom)
    • TALK SUMMARY: Correlation does not imply causation—but a narrow focus on hammering this catchphrase home to applied researchers may have left many of them ill-equipped to tackle the causal inference problems they will inevitably encounter in their work. Across fields, researchers often fail to realize that they are asking a causal question in the first place, and even if they do, they may lack the toolkit to arrive at a coherent answer. How can we as a scientific community do better? In my talk, I will discuss various (hopefully) helpful ways forward, with a special focus on what the more technically inclined can do to help applied researchers—potentially afraid of anything related to statistics—improve their inferences.
    • REGISTER HERE
  • Humanities and Data Science interest group: CALL FOR ABSTRACTS. Conference: Quantitative Diachronic Linguistics and Cultural Analytics, 15-16 January 2026, King’s College London (Strand Campus, WC2R 2LS)
    • We invite submissions for the conference Quantitative Diachronic Linguistics and Cultural Analytics: Data-Driven Insights into Language and Cultural Change. The conference is funded by the London Arts & Humanities Partnership.
    • For more information, see the conference webpage