Cloud Based Digital Twin Developer

You’ll play a pivotal role in developing and implementing a novel hybrid diagnostic and prognostic models for SEITL’s gas turbines. The KTP aims to deploy the models on a scalable cloud platform to analyse real-time operational data.

By working alongside SEITL’S industry leaders and academic experts from the University of Lincoln, you’ll contribute to designs that meet real industrial needs while embedding cutting-edge knowledge within the company. This unique multidisciplinary project will empower you to make a lasting impact.

What We’re Looking For

• Practical experience of programming Python and Matlab.
• Experience of mathematical/physical/hybrid modelling
• Experience in deploying intelligent algorithms
• Some thermodynamic modelling and/or knowledge of gas turbine technology is desirable, but not essential
• You will be able to interpret and clearly articulate technical and complex information.
• You will be expected to present to a wide-ranging audience including senior stakeholders.
• You will be proactive, able to influence others and build rapport quickly, developing long term relationships.
• You will enjoy responsibility, solving unexpected problems and challenging the status quo.

The aim of the KTP is to develop and deploy a cloud-based digital twin for medium-sized industrial gas turbines in order to facilitate anomaly detection and prognostics. The project will provide a critical step in commercializing the underpinning technology and provide a new suite of predictive service offerings to customers.