Research Fellow

University of Birmingham - College of Engineering and Physical Sciences, School of Engineering

Fixed-term until 31 October 2018

RE-TRAC - Real Time Traffic Speed Condition Survey

RE-TRAC is a collaboration between HSL Ltd. and the University of Birmingham to develop a multi-sensor platform to assess the condition and deterioration of local roads. 

RE-TRAC will develop an automated process to collect and analyse road cracking and fretting (surface deterioration which leads to potholes) data at much higher levels of accuracy than current slow and expensive visual surveys using a suite of sensor technologies. The resulting information will improve asset management decision making and thereby yield a better return on road maintenance spending, facilitating the preservation of our local roads and reducing, through improved road condition, road use costs.

The post will focus on i) identifying and trialling a number of existing sensor technologies, which can be used in isolation or combination to obtain information relating to cracking and fretting from road surfaces under a variety of operating conditions and ii) developing computer based algorithms to process the data from the sensors so that the type and extent of cracking and fretting can be measured accurately and categorised. 

The field work will involve trialling an array of different existing types of sensor technologies, such as lasers, high-frequency GPR and 3 video imaging. The computer based work will use the data collected from the field trials to develop tailored data processing and interpretation strategies, utilizing computer vision, signal processing and machine learning techniques to enable all types of cracking and fretting to be identified and categorised at various stages of their development and under a variety of operating conditions present during data capture.

Based in the Department of Civil Engineering, you will take a lead in delivering project outcomes. You will contribute to publishing the findings as they emerge in leading international journals, liaising closely with the other partners on the project, and will work within a leading research group gaining extensive industrial and academic contacts and experience.

You will have a good understanding of different signal processing techniques which may be pertinent to a variety of sensor technologies, in particular those useful for GPR data, video image analysis or laser reflection data, and the ability to use Matlab.  The successful applicant will be expected to have a range of skills related to signal processing using traditional approaches (filtering, signal enhancement, segmentation, pattern recognition, feature extraction, measurement and description) and/or machine learning (e.g. neural networks, evolutionary computation). 

You will have experience of publishing research findings in international journals and/or conferences. You will have a first degree in computational science, engineering, mathematics, or a related discipline, with a relevant higher degree being an advantage.  A UK driving license would be an advantage as there will be a need to travel to field trial locations. The post-holder would be expected to assist other research projects within the Department and contribute to the success of the Department through a range of activities such as teaching, open days and external engagements.

Informal enquiries can be made to Dr Michael Burrow;

To download the details of this position and submit an electronic application online please click on the Apply Online button below, please quote Job Ref 58023 in all enquiries.

Valuing excellence, sustaining investment

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Midlands of England