UKRI Centre for Doctoral Training in Artificial Intelligence, Machine
Learning & Advanced Computing
Training
Our CDT provided a training environment in which doctoral researchers working on a research topic in, say, health informatics, particle physics or deep learning, were able to exchange interdisciplinary methods and tools, and hence dramatically enhance the research environment. This was achieved employing a mixture of in-person and virtual meetings, mentoring schemes across the cohorts and institutions, and the co-development of projects, including peer-to-peer learning.
Some key components were:
- Taught components in Year 1, consisting of a selection of foundational modules in AI and computing, to establish a common knowledge base, and optional modules, specific to the research theme and the institution.
- Computing and data specific skills, developed in a hands-on fashion, via the Software Carpentry and an extended coding challenge.
- Residential meetings, to further develop a coherent community across the institutions. The meetings included scientific presentations, transferable skills training and engagement with external partners.
- Responsible innovation, to link creativity and opportunities in science and innovation with a sense of social responsibility.
- Placements at external partners, woven throughout the four-year programme. This included a six-month placement in the second half of the PhD.
