I'm looking for a strong PhD student candidate to nominate for application to the EPSRC DLA (Doctoral Landscape Award) studentships, which commence October 2027. The deadline for nomination is end of January 2027, and the award would be sited in the School of Computer Science at the University of Nottingham, UK. The DLA funding favours home students (i.e., UK citizens, however exceptional international students may be considered).
The topic I'm interested in supervising is about studying software developers' practices with "AI tools" (i.e., LLM-based assistance) and mapping out its implications. This is an extremely live area of research, with new work being published frequently, all against a background of contentious claims (e.g., that human developers are "redundant"). The problem is that much of the present research tends to avoid spending time on deeply interrogating how AI tools are practically integrated into the everyday work practices of software developers and their teams. This is probably because doing so - making sense of the intricate activities of software developers - is frankly rather hard. But doing so is vital, because it is only through attention grounded in practice that we can sensibly map out what the future looks like for the advancement of software development tools, reformulate teamwork practices themselves, and correspondingly push the evolution of software development education and the wider teaching of computer science as a discipline. There are many fascinating features that this PhD could address, all of which seek the socially organised foundations of such practices; for instance: how the mundane work of reading code is respecified by AI tools, how these tools are integrated into / change existing toolchains and workflows, how tool output or toolic code interventions are treated and transformed / manipulated by developers, or how the social organisation of development comes to be reassembled around differences produced by AI programming tools..
This PhD would use ethnomethodology and conversation analysis (e.g., see Reeves 2019) as a means to get at the praxeological composition of software development work, as it is lived and experienced by developers, and begin to reveal what is really entailed when people say "I used AI to develop this". As such the ideal candidate for this PhD would be someone who is familiar with programming / software development in some capacity but also has sociological interests, a willingness to engage in observational research, and an interest in the integration of technical understandings / competencies with their socially organised foundations.
The DLA is highly competitive, and we can only nominate a small number of students from UoN Computer Science. If you are interested in pursuing this opportunity, and if you think you are a good fit for the PhD area, please contact me directly: stuart.reeves@nottingham.ac.uk (latest contact by mid Dec 2026).