PhD Studentship: Adaptive Human-Robot Teams for Mobile I&M Across Dynamic Environments

PhD Studentship available on the RAINZ CDT programme at the University of Oxford. 

Project Overview 

• Project title: Adaptive Human-Robot Teams for Mobile I&M Across Dynamic Environments
• Supervisors: Prof Nick Hawes 
• Cohort research challenge: Long-term autonomous monitoring and maintenance of assets
• Year 1 MSc Course: MSc Artificial Intelligence
• Year 2 – 4 PhD Location: University of Oxford  

Abstract: This project explores long-term collaboration between a fixed human-robot team performing repeated similar inspection and maintenance (I&M) tasks across varying environments. Unlike traditional approaches focused on static, single-site deployments, this project will investigate how an operator-mobile robot pair can adapt to new or revisited sites with differing layouts, constraints, and uncertainties, within the same task context (e.g. a specific I&M specification). Key challenges include dynamic task and action allocation between the human and robot; developing strategies for managing environmental uncertainty; and designing intuitive interfaces for instruction and feedback within the human-robot team. The goal is to enable scalable, contractor-style service delivery models powered by autonomous robotics. 

About the RAINZ CDT 

The EPSRC Centre for Doctoral Training in Robotics and Artificial Intelligence for Net Zero is a partnership between three of the UK’s leading universities (The University of Manchester, University of Glasgow and University of Oxford). 

Robotics and Autonomous Systems (RAS) is an essential enabling technology for the Net Zero transition in the UK’s energy sector. However, significant technological and cultural barriers are limiting its effectiveness. Overcoming these barriers is a key target of this CDT. The CDT’s research projects will focus on how RAS can be used for the inspection, maintenance and repair of new infrastructure in renewables (wind, solar, geothermal, tidal, hydrogen) and nuclear (fission and fusion), and to support the decarbonization of existing maintenance and decommissioning of assets. 

We are seeking motivated and curious graduate scientists and engineers who are interested in developing new skills and have a desire to help increase use of RAS to support the decarbonisation of the energy sector. RAINZ CDT students will play an important role in advancing this rapidly growing area of science and engineering. 

Funding: 

This 4-year studentship covers tuition fees at Home student rate, a tax-free stipend, and a Research Training and Support Grant. As part of TechExpert, successful Home applicants receive an additional £10,000 annual stipend enhancement.  

Funding for this project is provided by the EPSRC and MTC.  

Eligibility 

Applicants should hold a First or strong Upper Second-class honours degree (2:1 with 65% average), or international equivalent, in Engineering, Computer Science, Physics, Mathematics, or a related discipline. Applicants should also demonstrate evidence of programming experience. applicants for this project are expected to have strong programming and discrete mathematics skills, together with experience or interest in developing computational models of autonomous systems (e.g., using Markov decision processes, logic, graphs, etc.). This project is only open to British citizens. 

How to Apply 

Applications should be submitted through the RAINZ CDT website via the above 'Apply' button by 13 February 2026, where further information about the CDT is also available. Informal enquiries can be made by emailing rainz@manchester.ac.uk. 

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