The AIRS-NFM project aims to determine whether the manufacture of nuclear fuel can be rendered responsive, using applied gamma-ray spectrometry, responsive high-resolution imaging and digital twinning, to reduce waste, disruption, energy consumption and increase efficiency, resilience and the sustainability of nuclear fuel production. It is a collaboration between Lancaster University, the University of Strathclyde, Westinghouse Springfields Fuels Ltd., National Nuclear Laboratory and Mirion Technologies Ltd. This role is part of this significant investment made in this project by EPSRC, with this appointment being based at Lancaster and including secondments onsite at Springfields. It concerns the role of Research Associate that will focus on the data-driven, adaptive condition monitoring and response control using machine learning central to the objectives of AIRS-NFM.
You should have a PhD in Engineering (or equivalent) with a strong background in experimental scientific research with condition monitoring, data driven modelling and applied systems control. Experience of sensor technology, using embedded data acquisition systems and software programming, the fundamental manufacture of nuclear fuel, collaboration (both academic and industrial) and of working in multinational teams to strict deadlines, is highly desirable.
The overall project is led by Prof Malcolm Joyce and the specific aspect of this research is led by Dr Xiandong Ma and Prof C. James Taylor. You will be joining the highly-regarded and dedicated research group of engineers and scientists working in a well-equipped, laboratory-based research environment.
You will join us on an indefinite contract however, the role remains contingent on external funding which, at this time is due to come to an end on 31 August 2024.
The University is a member of the Athena SWAN Charter, which recognises and celebrates good employment practice undertaken to address gender inequality in higher education and research.
Closing Date: 30 Jun 2021
Category: Research
