Interpretable Data-Driven Modelling of Fuel Cells

Imperial Enterprise; Greater London; On-site; GBP 38,000 - 48,000; Full time

Benefits offered by this job

39 days off a year

Generous pension schemes

Job summary

Imperial College London invites applications for a Research Assistant or Associate in Data-Driven Modelling of Fuel Cell Dynamics. The role supports an Airbus- ATI-funded project to develop data-driven modelling methods for hydrogen-powered aircraft, focusing on nonlinear dynamics and interpretable reduced-order models using SINDy.

The successful candidate will work with the Chemistry group and Mechanical Engineering group, contributing to modelling, data analysis, and validation with numerical

Qualifications

• Strong background in fuel cell systems and the numerical modelling of electrochemical systems.
• Experience in machine learning and data-driven modelling.
• PhD or equivalent research experience in a relevant field.

Responsibilities

• Develop nonlinear dynamic models of fuel cell electrochemistry and interpretable reduced-order models using SINDy.
• Work with the Chemistry group and Mechanical Engineering group to analyse numerical and experimental data.
• Contribute to improving design, control, performance and reliability of fuel cell systems.

Skills

Fuel cell systems

Numerical modelling

Machine learning

Data-driven modelling

Education

PhD in Aerospace Engineering, Chemistry, or related discipline

Master's degree in Aerospace Engineering, Chemistry, or related discipline

Job description

Imperial College London invites applications for a Research Assistant or Associate in Data-Driven Modelling of Fuel Cell Dynamics. The role supports an Airbus- ATI-funded project to develop data-driven modelling methods for hydrogen-powered aircraft, focusing on nonlinear dynamics and interpretable reduced-order models using SINDy.

The successful candidate will work with the Chemistry group and Mechanical Engineering group, contributing to modelling, data analysis, and validation with numerical