Research Associate (AI-Enhanced Predictive Modelling and ...

Teesworks; Tees Valley; Hybrid; GBP 32,000 - 42,000; Full time

Job summary

Teesside University invites applications for a Research Associate to join an externally funded project focused on AI-enhanced predictive modelling and optimisation for offshore cable systems and related components.

You will develop AI models, uncertainty quantification methods, and optimisation algorithms, handling engineering data and integrating solutions within an engineering software platform with university and industrial partners.

Responsibilities

• offshore cable modelling and engineering simulation
• engineering data processing and analysis
• AI and machine-learning model development
• uncertainty quantification and reliability assessment
• AI-driven optimisation, model validation, and software integration

Job description

Research Associate (AI-Enhanced Predictive Modelling and Optimisation)

Applications are invited for a Research Associate to join an externally funded collaborative research project focused on developing AI-enhanced methods for the reliability assessment and optimisation of offshore cable systems, cable protection systems (CPS), and associated components.

The Research Associate will develop and validate AI predictive models, uncertainty quantification methods, and optimisation algorithms for the reliability assessment and optimisation of offshore cable systems, cable protection systems (CPS), and associated components. The postholder will process engineering simulation data, develop AI-based predictive and optimisation methods, and support their integration and validation within an engineering software platform, working closely with university researchers and industrial partners.

The successful candidate will contribute to:

• offshore cable modelling and engineering simulation;
• engineering data processing and analysis;
• AI and machine-learning model development;
• uncertainty quantification and reliability assessment; and
• AI-driven optimisation, model validation, and software integration.

For more information, please review the Job Description and Person Specification.

This position is “Subject to having the grant agreement in place”.

Please be advised that due to the minimum salary thresholds imposed by the UKVI, this post may qualify for University sponsorship under the Skilled Worker visa route.

If you are shortlisted, your interview will take place via Microsoft Teams. Please note that the University may ask you to participate in a number of selection activities as part of the recruitment process for this vacancy.

Interview date – Friday 2 October 2026

Please note that we are advertising this vacancy on other websites but we are not using those third parties to collate applications for us. If you are viewing this advert on a third party website please ensure you apply directly to Teesside University (https://www.tees.ac.uk/sections/jobs/index.cfm)