Overview
The Rolls-Royce University Technology Centre for Computational Engineering is delighted to announce the recruitment of two research fellows. Working as part of a multi-partner Innovate UK funded project we are seeking highly motivated individuals to join us in the development of digital engineering technologies to accelerate the design of the next generation of gas turbine engines.
Responsibilities
* Develop novel ML/DL methods which leverage both computational and experimental data to accelerate gas turbine design and improve through-life performance predictions.
* Collaborate with industrial partners to develop methods that accelerate gas turbine design and improve through-life performance predictions.
* Develop ML/DL methods for engineering in collaboration with industrial partners and disseminate research within high-impact journals and at international conferences.
* Utilise numerical modelling (e.g., CFD and FEA) and work as part of a team on a multi-partner project.
Qualifications
* PhD or equivalent in a relevant discipline.
* Experience in the development of machine/deep learning (ML/DL) methods for engineering.
* Experience in numerical modelling (e.g., CFD and FEA).
* Experience working as part of a team, with industry, and disseminating research within high-impact journals and at international conferences.
Contract details
This full-time post will be offered on a fixed-term contract until the 30th September 2028.
Enquiries
Informal enquiries may be addressed to Prof. David Toal, by email djjt@soton.ac.uk. Please note that applications sent directly to this email address will not be accepted.
Equality, diversity and inclusion
We are committed to equality, diversity and inclusion and welcome applicants who support our mission of inclusivity.
How to apply
Apply by 11.59 pm GMT on the closing date. For assistance contact Recruitment on +44(0)2380 592750 or recruitment@soton.ac.uk quoting the job number.
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