Powered Predictive Maintenance

Aston University; Birmingham; Hybrid; GBP 40,000 - 42,000; Full time

Benefits offered by this job

£2000 development budget

25 days annual leave

Mentorship & guidance

Aston Wellbeing support

Job summary

Aston University invites applications for a KTP Associate to lead the development of an AI-powered predictive and prescriptive maintenance system for Genie UK's lifting equipment within the LiftConnect platform.

You will develop intelligent data-quality agents, deploy scalable predictive models, and build operational dashboards while ensuring methodologies, training and workshops are delivered to embed the solution commercially.

Qualifications

• PhD level in Artificial Intelligence, Machine Learning, Computer Science, Data Science, Control Engineering or related field.
• Experience leading technically complex predictive maintenance or industrial analytics projects.
• Experience with data-quality agents, predictive modeling across machine families, and prescriptive decision support.

Responsibilities

• Lead development of an AI-driven predictive and prescriptive maintenance system for Genie’s LiftConnect platform.
• Develop data-quality agents and transferable predictive models.
• Create prescriptive decision support and operational dashboards.
• Deliver methodologies, documentation, training and workshops for embedding the solution in the business.
• Coordinate with service, project management, organisational change, parts, data, telematics and commercial teams.

Skills

SQL & Power BI

Time-series analysis

Python (PyTorch/TensorFlow)

Cloud ML / AWS SageMaker

LLM development (RAG)

Industrial analytics

Business awareness

Data analysis tools

Education

PhD in AI/CS/Data Science

Tools

SQL

Power BI

AWS SageMaker

PyTorch

TensorFlow

Job description

KTP Associate in AI-Powered Predictive Maintenance

Aston Digital Futures Institute

Location: Genie UK, The Maltings, Wharf Road, Grantham, Lincolnshire, NG31 6BH (hybrid)

Salary: £40,000 to £42,000depending on experience plus £2000 per annum personal development budget

ContractType: Fixed Term(36 months)

Basis: Full Time

ClosingDate: 23.59 hours BST on Sunday 11 October 2026

InterviewDate: Monday 26 October 2026

Reference: 1368-26

ReleaseDate: Friday 25 September 2026

About this role:

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.

What you will gain:

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.

What we are looking for:

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:

• 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
• 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.

Additional Benefits and Support:

£2000 per annum for personal and professional development for the duration of the project

Annual leave (25 days p/a)

Professional support and mentorship

Mental health and wellbeing support: Aston Wellbeing

KTP Associates manage strategic projects, bridging the academic and business worlds, which can enhance and fast-track their careers. You will also benefit from expert coaching and mentoring. 60% of our KTP associates are offered employment by their host companies at the end of the KTP.

About this role:

This Knowledge Transfer Partnership, between Aston University and Genie UK Limited, gives you the chance to lead 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, turning telematics, onboard sensor data and historical maintenance data into actionable maintenance intelligence within Genie’s LiftConnect platform. You will work on a sector-leading project, with responsibility for developing intelligent data-quality agents, predictive models that can transfer across machine families, prescriptive decision support, operational dashboards and ensure delivery of methodologies, documentation, training and workshops needed to embed the solution in the business.

What you will gain:

You will lead a strategic project of direct strategic and commercial importance to the business. The role offers experience of developing a minimum viable product, working 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

This is a Knowledge Transfer Partnership (KTP) funded by Genie UK Limited and Innovate UK . KTPs are collaborative, three-way partnerships creating positive impact and driving innovation by linking businesses with the UK's world class knowledge bases to deliver innovation projects led by skilled graduates. It is essential you understand how KTP works and the vital role you will play if you secure this position. To learn more please visit: www.aston.ac.uk/ktp

Aston University: You will work in a project team with Prof Abdul Sadka and Dr Chao Liu from Aston University and the Senior Management Team at Genie UK with further support from an Innovate UK Knowledge Transfer Adviser.

The Business Partner:Genie is a world-leading manufacturer of equipment that solves customers’ aerial worksite challenges with five decades of industry leadership. It has a global presence supplying and maintaining a range of lifting equipment solutions from boom and scissor lifts to portable aerial work platforms. Its UK location is focussed on after-care, and this project offers the opportunity to play a leading role in a strategically important project for data-led aftermarket services.

Location:The Business Partner operates a hybrid working model but you will be based predominantlyat Genie UK’s premises in Grantham. You will also have access to facilities at Aston University in central Birmingham. Some travel to key clients may also be required. Therefore, you must live within a commutable distance.

To learn more about this role it is essential you refer to the Job Description documents. For informal enquiries about this role please contact Dr Chao Liu e-mail: [e-mail].

As users of the disability confident scheme, we guarantee to interview all disabled applicants who meet the minimum criteria for the vacancy.

The University celebrates the rights of freedom of speech and academic freedom and is committed to maintaining and protecting these rights within the law. An offer to work at Aston University will never be denied on the basis of an individual’s lawful expression of their beliefs, ideas or opinions.

Aston University is an equal opportunities employer and welcomes applications from all sections of the community. It promotes equality and diversity in all aspects of its work. We strive to have robust inclusivity strategies in place, to encourage colleagues to have the confidence and freedom to be themselves in the workplace. For more information, visit: https://www2.aston.ac.uk/about/inclusive-aston

Guidance on AI-Assisted Applications
While we cannot prevent applicants from using AI tools to support their application, we ask that all submissions reflect your own experience, achievements, and motivations. We want to understand what you personally bring to the role, so please ensure your application represents your own voice and capabilities.