Job title
Machine Learning Engineer for Predictive Maintenance (KTP Associate)
Job reference
REQ240282
Date posted
26/03/2024
Application closing date
21/04/2024
Location
Loughborough
Package
£35,000 - £42,000 per annum at a starting salary to be confirmed on offer of appointment
Job description
School of Aeronautical Automotive Chemical and Materials Engineering
Uniper UK Limited
Job title: Machine Learning Engineer for predictive maintenance (KTP Associate)
Salary will be between £35,000 - £42,000 per annum at a starting salary to be confirmed on offer of appointment. The successful applicant will also receive a £2,000 per annum training budget.
This is a full time, 24-month Knowledge Transfer Partnership (KTP) project between Loughborough University and Uniper UK Limited, funded by UKRI Innovate UK.
Due to the funding of this post, the associate must be in place to start work by 19th August 2024.
Project Title: To develop predictive maintenance technologies for gas turbine electricity generator monitoring, facilitating continuity in supply and energy grid stability.
Uniper operate seven power stations in the UK utilising a variety of energy generation sources. With a broad portfolio of assets supporting the energy sector Uniper have stakes in the Europe to UK 235-kilometer gas pipeline, UK regasification and gas storage facilities.
We are looking for a KTP Associate who will be a highly motivated, proactive and perceptive individual qualified to Master's level in engineering, computer science or a related discipline.
The successful candidate will ideally have experience of developing algorithms in relevant Engineering subjects as well as conducting research that can lead to high quality conference or journal publications. The ability to collaborate with a diverse team, and to proactively take the initiative is essential.
The KTP Associate will be based primarily at the company's premises, Uniper UK Technology Centre, Ratcliffe-On-Soar, Nottingham, and will also spend some time at Uniper Grain Power Station, Kent, as well as Loughborough University with the academic team.
The Associate will be supervised by an academic team, led by Dr Eve Zhang and Dr Miguel Martinez Garcia, who are experts in predictive maintenance and machine intelligence.
The Associate will form an integral part of Uniper's Gas Turbine fleet team, working closely with the company supervisory team and company partners.
As a KTP Associate, the successful applicant will have access to a wide range of commercial, R&D and management training programmes, as well as technical training resources and facilities at Loughborough University.
For more information refer to the Job Description and Person Specification.
Informal EnquiriesInformal enquiries should be made to the Lead Academic, Dr Eve Zhang ([email protected]).
The closing date for receipt of applications is 21st April 2024.
The interviews will take place in two stages: The first stage will be in the w/c 29th April 2024 for online interviews, and the second stage will be in-person interviews in the w/c 7th or 13th May 2024.