PhD Studentship: Machine Learning and Cloud Computing in the Dynamic Optimisation of Energy Efficient Autonomous Vehicles

Loughborough University

Application details:
Closing date for applications: 10 March 2018
Start date of studentship: July 2018

Primary supervisor: Dr Dezong Zhao
Secondary supervisor: Dr Byron Mason

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 Graduate School, including tailored careers advice, to help you succeed in your research and future career.

Find out more:

Project Detail:
The Department of Aeronautical and Automotive Engineering of Loughborough University is seeking a highly motivated graduate to undertake an exciting 3-year PhD project entitled “Machine learning and cloud computing in the dynamic optimisation of energy efficient autonomous vehicles”. 

There is an ongoing revolution in developing autonomous vehicles to greatly improve safety and traffic efficiency. This general trend is greatly impacted by advances in powertrains for improved vehicle fuel economy. The intersection of autonomy and green powertrain will shape the future of the automotive industry. Most leading automotive companies have announced strategic partnerships with IT companies to explore this area including Ford and Google; Toyota and Microsoft; General Motors and Lyft; and Volvo and Uber.

This PhD project aims to develop innovative methods on sensing, modelling, control, optimisation and computing for energy efficient autonomous vehicles. The project falls into a rapidly growing area and focuses on a class of far-reaching scientific and technical problems. Autonomous vehicles use perception of the environment to make decisions and realise unmanned driving. Low carbon vehicles strongly rely on the dynamic optimisation of powertrain behaviour. We aim to update the powertrain model with information about the driving environment, thus breaking down a wall that currently exists between research in autonomous driving and powertrain control.

In this project you will develop machine-learning-based modelling and dynamic optimisation methods. To tackle computational pressures, a cloud-computing-based framework is to be designed.

Through this project you will join one of the largest University-based automotive research groups in the world. You will have access to world-class vehicles and powertrains research facilities. You will also receive supports from experienced researchers and practitioners in the field.

Find out more:
For further project details contact Dr Dezong Zhao,

Entry requirements:
Applicants should have, or expect to achieve, at least a 2:1 Honours degree (or equivalent) in Control Engineering, Electrical & Electronic Engineering, Computer Science, Mechatronics, Mechanical Engineering, Vehicle Engineering or a related subject. A relevant Master’s degree and/or experience in one or more of the following will be an advantage: Artificial Intelligence, Programming skills (e.g. Matlab, C, C++ and Python).

Funding information:
The 3-year studentship provides a tax-free stipend of £14,553 per annum plus tuition fees at the UK/EU rate. International students may apply however the studentship will cover the international tuition fee only.

How to apply:
All applications should be made online at Under programme name, select ‘Aeronautical and Automotive Engineering’.

Please quote reference number: AAE-DZ-1804

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Midlands of England