Completed Engineering Education & Skills

DTA - University of Nottingham

In plain English

AI plain-English summary

The University of Nottingham is receiving funding to train the next generation of doctoral researchers across science and engineering disciplines. This grant supports a Doctoral Training Partnership (DTP), a mechanism through which the Engineering and Physical Sciences Research Council (EPSRC) funds postgraduate education. The abstract does not specify a single research question or problem. Instead, the funding provides a flexible framework for the university to recruit and train PhD students across a range of topics within EPSRC's remit. The specific research projects will be defined by the students and their supervisors over the course of the programme. The impact of this grant is indirect but foundational. By producing highly skilled doctoral graduates, it strengthens the UK's research and innovation workforce. These individuals will go on to work in academia, industry, and the public sector, contributing to advances in areas such as manufacturing, energy, computing, and healthcare technologies. The grant does not target a specific application or breakthrough; it is an investment in human capital and long-term research capacity. Similar training partnerships have historically underpinned many of the UK's scientific and industrial capabilities.

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

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DTA - Nottingham Trent University
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UDLA 2527 University of Nottingham

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.