PhD Studentship: Bayesian Machine learning for autonomous-driving systems

Application details
Reference number: AAE-CP-1819
Start date of studentship: 01 January 2019
Closing date of advert: 18 November 2018
Interview date: 20 November 2018

Supervisors
Primary supervisor: Dr Cristiano Premebida
Secondary supervisor: Dr Cunjia Liu

Full Project Detail
An autonomous vehicle comprises essentially the following modules: sensory data representation, sensor-fusion & perception (AI/ML based techniques), localisation, control & decision-making, and communication (V2X). Autonomous driving is a very exciting research area, multidisciplinary and will shape the future of mobility and the next generation of vehicles. So, there are numerous technological and research challenges to be resolved in autonomous driving era.

The goal of this PhD project is to develop a multi-sensory perception system to support autonomous driving and advanced driving systems. The main approaches will be based on Bayesian deep learning, 3D data-environment representation, probabilistic sensor-fusion and inference. This PhD project finds applications in many areas, such as: sensor fusion (camera, radar and 3D-LIDAR); object detection and classification using Deep Learning (eg: pedestrian, cyclists, cars); road detection; object/obstacle tracking; probabilistic/statistical machine learning; spatio-temporal inference.

The Loughborough University Centre for Autonomous Systems
The Loughborough University Centre for Autonomous Systems (LUCAS) has a wide range of expertise in unmanned /autonomous vehicles, focussing on the development and implementation of advanced control, planning, sensing and perception, and decision-making.

The research group has an excellent track record in the area of autonomous systems and received a number of grants in recent years. Loughborough University transport-related research portfolio is extensive, and amongst our accolades are seven prestigious Queen’s Anniversary Prizes, in recognition of our world-class research excellence. Our long-standing industrial partnerships allow us to work closely with some of industry’s key organisations including Rolls Royce, Jaguar Land Rover, Ford and Nissan.

Intelligent mobility and autonomous driving are more than simply an enabling technology. It represents a revolution in modern transportation, spanning in-vehicle, vehicle-to-vehicle and vehicle-to-infrastructure intelligence: across all modes of transport. At Loughborough, we are reimagining the shape of the next-generation of connected and autonomous vehicles.
Find out more: http://www.lboro.ac.uk/departments/aae/research/imas/

Find out more
For further project details contact Dr Cristiano Premebida ([Email Address Removed]), prefixing the email subject with the string [AAE2018 PhD Studentship].

Entry requirements
Applicants should have, or expect to achieve, at least a 2:1 Honours degree (or equivalent) in Automotive Engineering, Aeronautical Engineering, Electrical and Computer Engineering, Computer Science, or a related subject. A relevant Master degree and/or experience in one or more of the following will be an advantage: machine learning, artificial intelligence, mobile robotics, sensor fusion, programming skills (such as Matlab, Python, ROS). Motivation and commitment are key ingredients.

Contact details
Name: Dr Cristiano Premebida
Email address: [Email Address Removed]
Telephone number: (+44) 01509227331

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

Please quote reference number: AAE-CP-1819