Centre for Doctoral Training

This programme provides training in data intensive methods and how to apply them in particle physics, gravitational physics and astronomy.

It has strong links with local industry and all students will undertake a six-month industrial placement.

The centre is led by Cardiff University jointly with the University of Bristol and Swansea University. It forms part of a national network of centres awarded funding in 2017 by the Science and Technology Facilities Council (STFC).

PhD course

Students will be enrolled at either Cardiff University, the University of Bristol or Swansea University for the duration of their four-year PhD. Working closely with UK industry, the course offers a unique opportunity to develop advanced knowledge of data intensive methods. You will have the opportunity to apply this knowledge to cutting edge problems in physics and astronomy as well as industry.

Specialist training in data intensive science will allow you to address scientific questions across particle physics, gravitational physics and astronomy. Our aim is to develop a training ground for the next generation of data scientists required by both industry and academia.

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Course structure

Year 1Induction workshop
Academic training in data-intensive science
Residential workshops
First research project
Two-week industry engagement opportunity
Year 2Academic research
Residential workshops
Project selection and scoping exercise with partner organisation
Year 3Academic research
Six-month industry placement
Year 4Complete research project
Write and submit thesis

Training in data-intensive science

The first year of the PhD will include formal training in data-intensive science, delivered through live-streamed video lectures, residential workshops and locally taught data-intensive science courses.

Live-streamed video lectures

All students will participate in a core taught programme of three courses, one from each university:

  • Advanced data analysis techniques delivered by Cardiff University, including Bayesian methods, MCMC routines, bootstrapping and multi-variate analysis.
  • Data visualization delivered by Swansea University, reviewing data dimensionality, data types and the visualization pipeline, and covering information, volume and flow visualization techniques.
  • Introduction to machine learning delivered by the University of Bristol, introducing different learning algorithms, the use of machine learning algorithms for solving classification problems as well as understanding the theoretical limitations of machine learning.

Residential workshops

Students will receive additional training through dedicated two-day workshops. Each workshop will provide specialist training in a specific area. There will be additional workshops around careers guidance, communications and scientific outreach.  The workshops will be delivered by experts from the three partner universities in collaboration with external partners.

Local data-intensive science courses

Students will be expected to take three additional courses at their host university.

Industrial placements

All students enrolled in the programme will undertake a minimum six-month placement during the third year of their PhD. Placements will give students an opportunity to apply their knowledge and broaden their career horizons while making a positive contribution to the work of their host organisation.

The placement will begin in January of the third year of the student's PhD and conclude by September. Students will be encouraged to engage with industrial partners from the first year of their PhD through events at residential workshops. Provision will also be made for short placements with partner organisations during the first and second years of the PhD.

During the placement, the student and supervisor will maintain contact on a monthly basis. In addition, a member of the student's supervisory team will visit the student once during their placement to monitor progress and welfare.