Completed Engineering Mathematics & Statistics

DTA - University of Oxford

In plain English

AI plain-English summary

The University of Oxford is training the next generation of researchers through a Doctoral Training Partnership funded by the Engineering and Physical Sciences Research Council. This matters because the UK needs a steady pipeline of skilled scientists and engineers to keep its research base strong and its economy competitive. Without sustained investment in postgraduate training, the country risks falling behind in the technologies and discoveries that underpin everything from faster computer chips to cleaner energy systems. The partnership supports PhD students across a range of engineering and physical sciences disciplines. These students will go on to work in universities, industry, and public-sector labs, where they will develop new materials, improve manufacturing processes, design better medical devices, and strengthen digital infrastructure. The impact is not immediate or visible in a single product, but it is structural: a trained workforce that can tackle problems society has not yet encountered. This is a training grant, not a research project with a specific scientific question. Its success is measured in people, not papers.

View original technical description
Doctoral Training Partnerships: a range of postgraduate training is funded by the Research Councils. For information on current funding routes, see the common terminology at https://www.ukri.org/apply-for-funding/how-we-fund-studentships/. Training grants may be to one organisation or to a consortia of research organisations. This portal will show the lead organisation only.

View the original record at the funder ↗

Researchers

Fran Sturley (Co-Investigator)Henry Cummins (Co-Investigator)Tim Softley (Principal Investigator)

Related Research

Grants with similar aims, by meaning.

DTA - Oxford Brookes University
DTA - University of Cambridge
DTA - University College London
DTA - Open University

Original classification

Training Grant

Plain English summaries and category classifications on this site are generated by AI and may not perfectly reflect the original research.