Early Stage Researcher: Thermoacoustic Instability Prediction

About the role

This is one of 15 Marie Curie ITN HyNOISE studentships across Europe, hosted by the Department of Engineering at the University of Cambridge. It aims to optimise the design of hydrogen-fuelled gas turbine injectors so that combustors are quiet and not susceptible to thermoacoustic instabilities. The project uses data assimilation, combining laboratory experiments (NTNU), large eddy simulations (TUB) and industrial experiments (RRD), with the university's adjoint-accelerated inference and optimization method (AXIOM).

Key responsibilities

• Extend AXIOM to typical hydrogen flame geometries using data from a laboratory-scale combustor at NTNU, with Bayesian model selection.
• Extend AXIOM to industrial-scale geometries using data from a real gas turbine fuel injector on an industrial test rig at RRD, using Bayesian experimental design.
• Develop and test several candidate mean field flame models with TUB, then assimilate LES data into them with AXIOM.
• Assimilate experimental data from the laboratory combustor and the RRD test rig into thermoacoustic and flame models.
• Optimize burner design to reduce susceptibility to thermoacoustic instability.
• Carry out a secondment at TU Berlin (about 2 months) and another at ETH Zurich (about 2 months).

Required profile

• MSc or equivalent in aerospace engineering, mechanical engineering, physics or a similar field.
• Ability to work efficiently and self-reliantly in a diverse, interdisciplinary and multicultural environment, and to work both in a team and independently.
• Proactive attitude and excellent written and spoken English.
• Willingness to travel for secondments and events.
• Candidates must not have spent more than 12 months in the UK in the 36 months before the PhD starts.

Required skills

• Solid knowledge of fluid mechanics and thermodynamics.
• Numerical analysis, simulation, optimisation and modelling tools.
• Computational fluid dynamics (CFD).

To apply, send a two-page CV and transcripts (if available) by 31 December 2026. Funding is conditional on securing a PhD place, applied for separately through the University's graduate admissions portal.