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Machine learning and data science are increasingly powerful and ubiquitous tools in materials research and development. This one-day workshop will focus on applications of these techniques within Polymer Science: as a means to effectively collate experimental data, to make predictions of physical properties, and as a tool to complement traditional computational and theoretical methods. We aim to explore the opportunities, limitations and dangers of such approaches, bringing together experimental, computational and theoretical researchers from the UK Polymer Physics community and beyond.

Invited speakers include:

Debra Audus, NIST (presenting online)
Paola Carbone, University of Manchester
Dr Tom McDonald, University of Manchester
Rampi Ramprasad, Georgia Institute of Technology
Eleonora Ricci, University of Edinburgh
Nick Warren, University of Sheffield

There will also be space for a small number of 15 minute presentations, with priority given to early career researchers: please contact Daniel Read (d.j.read@leeds.ac.uk) or Johan Mattsson (K.J.L.Mattsson@leeds.ac.uk) before 29 May 2026 if you would like to present. This meeting is kindly sponsored by the Institute of Physics and CCP5 (Collaborative Computational Project for computer simulation of condensed phases).

This is primarily an in-person event; however, if you are unable to join us in Manchester, you can register for an online place.

Key Dates:

Abstract submission deadline: 29 May 2026
Registration deadline: 8 June 2026

REGISTER ONLINE

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