KTP Associate in AI-Powered Predictive Maintenance

You will manage a strategic project of direct importance to the business. The role provides experience in developing a minimum viable product, collaborating with subject matter experts from service, project management, organisational change, parts, data, telematics, and commercial teams, and contributing to the launch of a new predictive maintenance service. You will receive day-to-day guidance from business and academic supervisors, along with access to Aston’s KTP Associate network, and a dedicated personal development budget to support your professional growth throughout the project.

Education, Skills and Experience

You should be educated to PhD level in a relevant field such as Artificial Intelligence, Machine Learning, Computer Science, Data Science, Control Engineering, or a related subject, and you should be able to demonstrate project experience in a technically demanding area. Skills and experience required for this exciting role include:

Essential

• Demonstrable experience in software tools for data analysis, such as SQL, Power BI, and cloud-based analytics environments
• Feature extraction and time-series analysis
• Probabilistic prediction techniques using scalable Python-based development environments such as PyTorch or TensorFlow
• Cloud-native machine learning and MLOps environments such as AWS SageMaker
• Small or large language model development with retrieval-augmented generation

Desirable

• Industrial analytics or predictive maintenance
• Knowledge of construction-related industries and market drivers
• Commercial awareness to connect technical development with business impact, budget awareness, and resource management

Attributes

• Strong research capability and the motivation to guide a technically complex project.
• Excellent communication skills to engage with stakeholders at various levels of technical knowledge and explain complex concepts clearly.
• Effective project and time management skills to facilitate a staged implementation.
• Ability to transform complex modelling work into deployable industrial solutions.

This Knowledge Transfer Partnership, between Aston University and Genie UK Limited, offers an opportunity to oversee the development of an advanced AI-driven predictive and prescriptive maintenance system for Genie’s lifting equipment. The project focuses on connected, partially connected, and non-connected machines, transforming telematics, onboard sensor data, and historical maintenance data into actionable maintenance intelligence within Genie’s LiftConnect platform. You will contribute to a sector-leading project, with responsibilities that include developing intelligent data-quality agents, predictive models that can transfer across machine families, prescriptive decision support, operational dashboards, and ensuring the delivery of methodologies, documentation, training, and workshops needed to integrate the solution into the business.