PhD Studentship: Machine Learning for Modern Vehicle Development

Application details:
Reference number: AAE-BM-2011
Start date: 01 January 2021
Closing date: 06 October 2020
Interview date: Shortly after the closing date

Intro:
Loughborough University is a top-ten rated university in England for research intensity (REF2014) and an outstanding 66% of the work of Loughborough’s academic staff who were eligible to be submitted to the REF was judged as ‘world-leading’ or ‘internationally excellent’, compared to a national average figure of 43%.

In choosing Loughborough for your research, you’ll work alongside academics who are leaders in their field. You will benefit from comprehensive support and guidance from our Doctoral College, including tailored careers advice, to help you succeed in your research and future career.

Find out more: http://www.lboro.ac.uk/study/postgraduate/supporting-you/research/

Project Detail:
Real world emissions, hybrid and fully electric vehicles together with the cloud-connected vehicles and a significant increase in on- and off-board computational capacity presents an opportunity for rethinking the way in which modern vehicle development is undertaken. Working alongside a billion-dollar global automotive supplier, this project is an exciting opportunity for a forward thinking and imaginative individual to participate in the design of new cloud-based automotive development processes.

Focussing on dynamic vehicle operation, the project will deploy modern Bayesian machine learning and statistical model identification techniques to automatically undertake experimental data collection, system model development and next-generation adaptive learning controller deployment. The resulting cloud-based development process will help OEMs manage increasing system and computational complexity in modern automotive systems.

The successful applicant will work within the Powertrains research group in the Aeronautical and Automotive Engineering Department at Loughborough University and benefit from an extensive range of experimental and high-performance computing facilities. In addition, there will be opportunity to work alongside our industrial partner including in their new state-of-the-art vehicle test facility.

Entry requirements:
Applicants should have a first-class honour in automotive/mechanical engineering or a related discipline (e.g. other engineering disciplines, computer science, physics, mathematics). Due to the technical nature of this project applicants should be able to demonstrate competence in at least one of the following: multi-objective optimisation, model predictive control, learning control, Bayesian statistics, machine learning and/or statistical (frequentist or Bayesian) model identification. Experience of programming in MATLAB/Simulink, Python or R is essential.

How to apply:
All applications should be made online at http://www.lboro.ac.uk/study/apply/research/
Under programme name, select Automotive Engineering

Please quote reference number: AAE-BM-2011