Machine Learning in soft and biological matter

Thursday 24 October 2019, 14.00-17.00
Organised by the IOP Computational Physics Group and IOP Polymer Physics  Group

Machine learning represents a radical new approach to many computational tasks which can be a valuable alternative to traditional physics-based simulation or multi-parameter data analysis. Additionally machine learning is being used to assist researchers by helping to direct and accelerate the exploration of parameter spaces, or even to accelerate directly computation itself.

This workshop is for researchers who would like to learn more about applying machine learning to their own field. We will start with speakers talking generally across multiple physical disciplines, before breaking into streams exploring materials research (including soft matter), plasmas and particle accelerators. Invited speakers include representatives from NVIDIA, the Alan Turing Institute and STFC, as well several university groups and the winner of the Computational Physics Thesis prize, Aldo Glielmo who used interpretable machine learning algorithms for two specific problems in condensed matter physics.

A multidisciplinary one-day workshop, the day is co-hosted by the Computational Physics group in collaboration with the Polymer Physics group, Particle Accelerators and Beams group and Plasma Physics group.


Richard Graham, University of Nottingham, UK

Alan Lowe, University College London, UK

Richard Clayton, University of Sheffield, UK

Dimitris Pinotsis, University of London—City and MIT, UK

Rollo Moore, The Royal Marsden NHS Foundation Trust, UK 

Ladislav Urban, The Royal Marsden NHS Foundation Trust, UK 

About the Groups

IOP Computational Physics Group

Computational physics may be broadly defined as 'the science of using computers to assist in the solution of physical problems, and to further physics research'.

Computers now play a role in almost every branch of physics and the following list provides some examples of areas that lie within the scope of computational physics:

  • Large scale quantum mechanical calculations in nuclear, atomic, molecular and condensed matter physics
  • Large scale calculations in such fields as hydrodynamics, astrophysics, plasma physics, meteorology and geophysics
  • Simulation and modelling of complex physical systems such as those that occur in condensed matter physics, medical physics and industrial applications
  • Experimental data processing and image processing
  • Computer algebra; development and applications
  • The online interactions between physicist and the computer system
  • Encouragement of professional expertise in computational physics in schools and universities

IOP Polymer Physics

The Polymer Physics Group provides a forum for all who have an interest in the physics of polymers.

The interests of the Group cover all aspects of the physical properties, structure and dynamics of polymers (both synthetic and naturally occurring) in the form of semi-crystalline solids, glasses, elastomers, gels, melts, and solutions. Fundamental phenomena are of interest along with applications of polymers in technologies, such as optoelectronics, photovoltaics, coatings, composites, medicine, foods and pharmacy. The Group works closely with The Royal Society of Chemistry and The Institute of Materials, Minerals and Mining. We enjoy close links with the Macro Group with whom we publish a joint newsletter. The Group welcomes physicists, chemists and engineers from both academia and industry.

Key dates

Registration deadline:

11 October 2019