ART-AI PhD Training Programme

Our 4-year integrated PhD programme trains “specialists with perspectives”, by including AI skills as well as a broader understanding of the engineering applications of AI and the ethical, policy and socio-economic consequences of intelligent technologies.

Key themes include:

transparency and intelligibility of AI
risk and decision making with AI
safety and trust in human-machine systems
policy-making with and for AI
innovation in data-driven and classical AI
engineering applications of AI
diversity and bias in AI

Programme structure

Our programme combines deep training in one discipline with integrated training across a breadth of disciplines. The course is designed around a 4-year full-time programme of study, starting in late September/early October each year, where students progress together as a cohort.

Year 1

Students follow the MRes in Accountable, Responsible and Transparent Artificial Intelligence programme that draws together AI and computer science, engineering and technology, and humanities and social sciences. The taught elements of the MRes year include units that are assessed using coursework and examinations (both oral and written). Students are required to reach a pass mark of 60% overall in order to progress onto the research phase.

Units

Students choose specialist courses in their “home discipline” and introductory courses in the other two disciplines, alongside four compulsory units:

Humans and intelligent machines
AI challenge
Interdisciplinary research preparation
Interdisciplinary thesis formulation report

The range of optional units to choose from includes:

Mathematics for AI
Machine learning
Robotics software
System modelling and simulation
Principles and skills of social research
AI as a social and political practice

Years 2-4

In years 2-4, students focus on their PhD research, under the guidance of a lead academic supervisor and at least one other academic. They take short courses on topics such as research software, and develop specific skills for their research interests.

Progress is monitored by supervisors and the CDT Director of Training. Students are expected to submit progress reports every 6 months. At the end of year 2, students should submit written work (a report and a data management plan) and sit an oral assessment to be confirmed on the programme.

During the research phase, students come together with academic staff and CDT partners in masterclasses and conferences building a wider network of peers and potential employers. Students have opportunities to go on a placement and research visits to a project partner.

The final stage of the PhD is submission of a substantial thesis and an oral or viva voce examination, in which students are required to defend the thesis to a Board of Examiners.

As this is an integrated programme, graduates receive both the MRes and the PhD certificates together at the end of the course.