Active Education & Skills

DTP 2224 University of Glasgow

In plain English

AI plain-English summary

This grant funds postgraduate training for doctoral students across a range of scientific fields, not a single research project. The funding supports the next generation of researchers through the University of Glasgow’s Doctoral Training Partnership. Rather than addressing a specific knowledge gap, it provides the infrastructure—stipends, supervision, and training programmes—that allows PhD students to pursue their own investigations in areas aligned with EPSRC’s priorities, such as engineering, physical sciences, and technology. If successful, this training pipeline will produce skilled scientists and engineers who go on to work in academia, industry, and the public sector. The impact is indirect but cumulative: every new material, medical device, or energy system that emerges from UK research depends on people who were once doctoral trainees. This grant does not aim for a specific breakthrough. Instead, it sustains the human talent that makes future breakthroughs possible. Similar training partnerships have historically underpinned advances in fields from quantum computing to medical imaging, though no immediate application is promised here.

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 ↗

Related Research

Grants with similar aims, by meaning.

DTP - University of Glasgow
DTP 2224 University of Strathclyde
DTP 2224 University of Edinburgh
DTP 2224 University of St Andrews
DTP - University of Strathclyde

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.