KTP Associate - Research Engineer (Machine Learning)

University of the West of Scotland – School of Computing, Engineering & Physical Sciences

Paisley campus

EDC Scotland Ltd (Erskine)

Salary per annum: up to £40,000 plus £5,000 personal development budget and the opportunity to do a higher degree at no cost

Full time: 42.5 hours per week

Fixed term: 30 months

We are seeking a Research Engineer with expertise in Machine Learning to join an innovative Knowledge Transfer Partnership (KTP) project between the University of the West of Scotland (UWS) and EDC Scotland Ltd. This project is focused on developing and deploying Machine Learning algorithms to extend the capabilities of the company’s newly developed DART (Drive Analysis and Remote Telemetry) product.

Essential skills required for the KTP Associate:

• Minimum MSc/MEng in Computing Science, Electrical/Electronic Engineering, or a related field.
• Experience in Python, Database Systems (e.g., MySQL, NoSQL).
• Knowledge of Cloud Computing platforms (e.g., AWS, Azure, Google Cloud) for deploying scalable and secure Machine Learning solutions.
• Experience in DevOps/MLOps.
• Experience of handling large and complex data.
• Experience of using open-source libraries e.g. PyTorch, Tensorflow.
• Knowledge of project management, automation, and process optimisation.
• Strong collaboration, communication and stakeholder engagement skills, with the ability to explain technical concepts to non-technical stakeholders.
• Analytical and problem-solving abilities.

About the project:

The aim of this KTP project is to develop Physics Inspired/Guided Machine Learning algorithms for predictive analytics and fault detection in large industrial machinery. This will facilitate early warnings and interventions for EDC Scotland customers, thus minimising downtime and preventing catastrophic equipment failure. Standard Machine Learning algorithms demonstrate exceptional abilities to find patterns that can be indicative of faults in large amounts of data but will often fail in limited data scenarios. By combining a hybrid approach combining Physics Inspired, Physics Guided and conventional Machine Learning this project aims to develop novel solutions to deploy with in the companies DART (Drive Analysis and Remote Telemetry) product.

If you have questions about this vacancy contact:

Professor Gordon Morison email: gordon.morison@uws.ac.uk

About the Company:

EDC Scotland specialises in ABB motors, ABB drives, variable speed drive repair, variable speed drive hire, inverter training and energy surveys. An ABB Authorised Value Provider, we repair, service, install, commission and sell inverters, motors and ABB control gear. Working with several blue-chip companies in the distilling, manufacturing, chemical and food and drink industries. With targeted investment in research and development the company have created DART (Drive Analysis and Remote Telemetry) their state-of-the-art drive monitoring system.

About KTP:

This position forms part of the Knowledge Transfer Partnership (KTP) funded by Innovate UK. It’s essential you understand how KTP works with business and the University, and the vital role you will play if you successfully secure a KTP Associate position. Please visit: www.uws.ac.uk/business/knowledge-expertise/knowledge-transfer-partnerships

Why UWS?

KTP is a strategic priority at UWS. The only Scottish University with a dedicated KTP Centre dedicated to supporting your KTP and professional development journey, UWS is #1 in Scotland for management KTPs and top-10 in the UK by size of our KTP portfolio.