The Centre supports data-intensive research across the Department of Physics. Its five research communities, Light, Matter, Physics of Particles, Physics of the Universe, and Space, Plasma and Climate, share many computational problems even where the science differs. These include statistical inference on large datasets, simulation-based methods, machine learning under physical constraints and real-time analysis.
Training
Data-intensive physics needs researchers who combine physical understanding with skills in statistics, machine learning and scientific computing.
The Department offers the MRes in Machine Learning and Big Data in the Physical Sciences, a one-year Master’s course in which students learn to apply machine learning and data-science techniques to real experimental data and carry out an extended research project.
The Centre supports project work and teaching connected with the course.
We also run onboarding and practical workshops for researchers and students using our systems, covering software environments, workflows and reproducible computing.
Partnerships
We welcome collaboration with academic groups, national facilities, industry and public organisations. Partnerships can involve joint research projects, specialist training, placements, facilities, datasets or software. Contact us to discuss ideas.