| Qualifications |
Duration |
Start dates |
Application period |
PhD
(MPhil also available) |
Full-time: 3–4 years
Part-time: 6–8 years |
February and October |
January to April |
Qualifications
PhD (MPhil also available) |
Duration
Full-time: 3–4 years
Part-time: 6–8 years |
Start dates
February and October |
Application period
January to April |
We have many leading roles in major international sky survey projects throughout the electromagnetic spectrum, including Euclid, Vera C,Rubin Observatory, LOFAR, Athena, JWST, ALMA, JCMT and more. These projects often create very large, very complex datasets, approaching the scale and complexity of the “Big” petabyte-scale datasets encountered by terrestrial high-technology industries. The  will generate two Exabytes per year, for example.
This has driven an rapid growth in artificial intelligence / machine learning and other data mining technologies in astronomy. We have led the application of many AI techniques to mining giant astronomical datasets, including finding strong gravitational lenses (using convnets), deconvolving and super-resolving far-infrared extragalactic images (using autoencoders), predicting multi-wavelength JWST images of high-redshift galaxies (using generative adversarial networks), and finding star-forming clumps in distant galaxies (using convnets). We collaborate with leading AI/ML computer scientists in the , and the .
Entry requirements
Minimum 2:1 undergraduate degree (or equivalent). There are also some DISCnet-specific entry requirements. If you are not a UK citizen, you may need to prove your .
Current/recent research projects
We are part of the DISCnet consortium, a nationally top-rated Centre for Doctoral Training that has funded ten OU PhD students in data-intensive science projects including astronomical applications of machine learning. All our DISCnet PhD students have two 3-month industry placements. In total DISCnet has run over 50 placements in 40 organisations and led to the founding of two start-up companies, recognised through three national prizes for real-world impact on local and national economies.
Potential Supervisors
Fees and funding
| UK fee |
International fee |
| Full-time: £4,786 per year |
Full-time: £15,698 per year |
| Part-time: £2,393 per year |
Part-time: £7,849 per year |
Some of our research students are funded via the UKRI Science and Technology Facilities Council (STFC) Doctoral Training Partnership; others are self-funded.
For detailed information about fees and funding, visit Fees and studentships.
To see current funded studentship vacancies across all research areas, see .
Links