Postgraduate Research Opportunity

Predictive maintenance of a COTS robotic system in Nuclear environments

About this studentship

Robot teleoperations are a key tool for interventions in high radiation environments, such as nuclear decommissioning and Nuclear Fusion power plant maintenance. However, exposure to radiation is detrimental to a robot’s electronic control systems, causing cumulative damage over time, risking the integrity of components, sensors, and the overall performance of the system. This project will focus on the predictive maintenance of a COTS (commercial off-the-shelf) robotic system to enable mission delivery.

The PhD project aim is to develop an on-chip monitoring system that obtains key hardware metrics from a System-on-Chip (SoC) module (e.g. currents, temperatures, voltages, etc.), and design a statistical and machine learning (ML) model to understand and predict when the board is starting to behave abnormally. The advantage of ML algorithms is that it can fine tune and predict failures without the need of exhaustive knowledge of each unique board and irradiation situation, providing some generality to the system. The monitoring can be performed at run-time without requiring a halt to the robot’s mission delivery. This research is also valuable to the research of fault mitigation systems, where error can be detected early and corrected quicker.

Providing the ability to reliably operate more complex electronic components in radiation fields is key to several sectors, including the delivery of cost-effective nuclear fusion powerplants and nuclear decommissioning of legacy sites and hardware.

Entry Requirements

The successful candidate would be expected to speak fluent English and meet our English Language requirements and will have a good honours BSc or BEng degree (1st) in computer science, electronic engineering or a related subject.

An MSc with Merit or Distinction is desirable (but not essential for students with a first-class degree). Strong analytical and mathematical skills are required, as well as good programming skills in C/C++ and/or Python. Knowledge of microprocessor architecture, machine learning, field-programmable gate array (FPGA), hardware description language (HDL), and/or embedded systems are desirable but not essential.

About Embedded and Intelligent Systems (EIS) Laboratory

As the member of Embedded and Intelligent Systems Laboratory at the University of Essex, the student will get access to the state-of-the-art of SoC devices and development as well as the data obtained from previous radiation chip tests undertaken as part of the RAI hub works and collaboration with advanced robotics group at NASA JPL. The student will have access to the irradiation facilities available to the University of Essex, at RAL, the Dalton Institute and NASA JPL to support their work.

We carry out research in the areas of Embedded Systems and System-on-Chip design with focus on security, power, performance and reliability, advanced embedded systems and processor architectures targeted for cyber physical systems, automotive/industrial, robotics, image processing, networked and distributed sensor nodes/Internet of Things and real-time critical systems. We have successfully pioneered what is now an industry leading solution with the technology for UltraSoC and Metrarc. Details about the research group and projects can be found in


The United Kingdom Atomic Energy Authority (UKAEA) is a UK government research organisation responsible for the development of fusion energy. UKAEA operates the JET tokamak on behalf of European partners and the UK’s own MAST Upgrade fusion experiment. UKAEA also leads the STEP (Spherical Tokamak for Energy Production) programme, which aims to design and build a demonstration fusion powerplant by the early 2040s. As the UK’s national fusion lab, the UK Atomic Energy Authority’s mission is to lead the commercial development of fusion power and related technology, and to position the UK as a leader in sustainable fusion energy.

RACE is a business unit of UKAEA. RACE’s mission is to make it possible to carry out tasks in hazardous and extreme environments. For future fusion power plants this capability is device defining and critical to commercial viability. The radiation encountered in such roles precludes human involvement and remote robotic operation and inspection over long periods of time is essential. RACE also works with academia and industry on bringing remote maintenance technology into other sectors such as decommissioning and space.

Funding scheme

This project is supported by the School of Computer Science and Electronic Engineering (CSEE) in the University of Essex and UK Atomic Energy Authority (UKAEA). The studentship will provide the PhD candidate with a costs of living stipend equal to UKRI rates, plus travel and training allowance and UK/International tuition fees.

How to apply

Please apply through our online portal.

During the application form, you will need to prepare a research proposal for this studentship topic as part of online application submission. Please mention the studentship title and potential supervisor names in your application. 

For general guidance on the application procedure please refer to our PhD application information.

Studentship application deadline: 31st May 2023