PRINZ: Privacy-Preserving Robotic Inspection of Net-Zero Infrastructure

About the Project

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.

Programme structure (1+3)*

Year 1 (Taught component):All students spend the first year at The University of Manchester undertaking taught MSc studies and bespoke CDT training. Students must achieve an average of 65% or higher in their MSc assessments to be considered for progression to the PhD component of the programme.

*Note: Students do not graduate with an MSc degree as the summer period is spent undertaking a CDT summer school rather than an MSc Dissertation.*

Years 2 – 4 (PhD research):Students are based at the host institution to undertake their PhD research (i.e., either The University of Manchester, University of Glasgow, or University of Oxford), which will be complemented by a comprehensive cohort-wide training and employability programme.

The RAINZ CDT programme follows a cohort-based training and research designed to ensure that graduates are not only subject matter experts, but also equipped with highly valuable skills in teamwork, sustainability, EDIA and wellbeing, industrial engagement, and commercialisation. Each cohort tackles an industry co-created, cross-sector challenge that requires a multi-disciplinary team of engineers and scientists to solve it. Researchers explore different aspects of the challenge, which are then integrated through the RAINZ CDT annual research sprints.

PhD Project Overview

• Cohort research challenge:Long-term autonomous monitoring and maintenance of assets
• Year 1 MSc CourseMSc Robotics
• Year 2 – 4 PhD Location: University of Glasgow

Research Abstract

The project’s aim is to ensure that robots can continuously inspect assets without creating privacy or surveillance risks for workers and nearby communities. To achieve this, the recruited PhD student will design sensing and data-handling pipelines that maintain inspection utility while systematically reducing privacy risk.

Autonomous inspection robots deployed around wind farms, solar arrays, or substations inevitably collect data about people (e.g., human workers) and neighbouring property. Long-duration autonomous monitoring and mission planning capabilities are increasingly mature [3], yet these systems introduce new privacy and acceptability challenges that can limit deployment. PRINZ will develop privacy preserving perception and data-management techniques tailored to long-term robotic inspection: e.g. on-device filtering, differential privacy [1], selective redaction [2], and access-controlled logging, combined with human-centred explanations of what data is captured and why. The work will consider what is minimally sufficient for asset monitoring while respecting data-minimisation and regulatory requirements.

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.

Please note this project is open to Home students.

EDIA

Equality, diversity, inclusion, and accessibility are fundamental to the success of the RAINZ CDT, and are central to all our activities. We recognise that a diverse research community enhances creativity, productivity and research quality, and contributes to greater societal and economic impact. We value applications from individuals of all backgrounds and identities.

We are committed to supporting work-life balance and offer flexible working arrangements to accommodate individual needs. Our selection process is designed to minimise unconscious bias, providing equal opportunities for all applicants.

How to Apply

Applications should be submitted through the RAINZ CDT website, where further information about the CDT is also available. Informal enquiries can be made by emailing rainz@manchester.ac.uk.

The deadline for submitting the RAINZ CDT application form is 5:00 pm, Friday 15 May 2026. Applications received after this deadline will not be considered.

Start Date:Monday 21 September 2026 (refer to The University of Manchester - Key Dates for more details).

Funding Notes

Funding:

Successful applicants will be awarded a 4-year studentship covering:

• Tuition fees paid at Home student rate*
• A tax-free stipend to help with living costs, set at the UKRI minimum rate** (i.e., £21,805 for 2026/27), which increases annually in line with inflation
• A Research Training and Support Grant to cover travel expenses and project consumables associated with your research including conference attendance, secondments, and other research and training activities

**TechExpert: As part of the UK Government’s TechFirst skills programme, Home students Cohort 2 of the RAINZ CDT will receive a £10,000 per year enhancement to their UKRI minimum stipend.