Knowledge Exchange Fellow Predictive Analytics at University of Strathclyde Business School UAE Abu Dhabi Full-time

is hiring a Knowledge Exchange Fellow Predictive Analytics at University of Strathclyde Business School UAE Abu Dhabi in Abu Dhabi, UAE. This is a full-time position.

Looking for Knowledge Exchange Fellow jobs in Abu Dhabi? University of Strathclyde Business School UAE is recruiting a Knowledge Exchange Fellow in Predictive Analytics within the Department of Electronic and Electrical Engineering. Additionally, this exciting 24-month fixed-term role involves developing prognostic and diagnostic techniques for health management of rotating machinery.

About the Role

The Knowledge Exchange Fellow will develop prognostic and diagnostic techniques for rotating machinery, using real-world data from existing vessels to inform future capability on next-generation models. Furthermore, you will work closely with industrial partners to develop a suite of analytics techniques demonstrating improved methods of understanding asset health. Moreover, this role involves experimental design, software development, and data science to predict and diagnose asset health conditions for a proactive condition-based monitoring strategy.

Key Responsibilities for Knowledge Exchange Fellow Predictive Analytics at University of Strathclyde Business School UAE Abu Dhabi

• Develop prognostic and diagnostic techniques for rotating machinery health management
• Lead knowledge exchange projects with industrial partners and stakeholders
• Apply as Principal or Co-Investigator for external knowledge exchange funding
• Conduct experimental design, software development, and data science research
• Develop predictive models and anomaly detection systems for asset management
• Write reports for external organisations and disseminate findings through publications
• Manage knowledge exchange projects from proposal through to delivery
• Collaborate with interdisciplinary teams across the Intelligent Systems division
• Engage with professional bodies and industry partners for knowledge transfer
• Contribute to the development of condition-based health monitoring strategies

Requirements

• PhD or equivalent in a relevant discipline such as engineering, data science, or AI
• Expertise in condition monitoring and asset management of engineering systems
• Strong track record in data science, handling and processing large data sets
• Experience in artificial intelligence, predictive modelling, and pattern recognition
• Software development and testing experience, ideally in rotational plant systems
• Demonstrated track record in developing knowledge exchange proposals and securing funding
• Security clearance (SC) eligibility is essential for this post