PhD Studentship On-water positioning and 3D environment mapping for river ecosystem monitoring using autonomous robotics



Application deadline: 9th December 2013
Supervisor: Dr Monica Rivas Casado

Duration of award: 3.5 years
Award type: PhD

Funded by  Magellium Ltd, The Environment Agency and EPSRC, due to funding restrictions this studentship will cover the tuition fees at the UK/EU rate only and provide a bursary of up to £15,500 p.a for three years*

Cranfield University have an exciting research opportunity concerning the use of recent advances in 3D environment mapping, computer vision and autonomous sensing to enable wide-area, long-duration sensing of the on-water environment for river ecosystem monitoring.

It builds upon recent research in both autonomous sensing problem of Simultaneous-Localisation and Mapping (SLAM) (Computer Vision, Dr. Toby Breckon) and environmental monitoring, (Water Science, – Dr. Monica Rivas).

This will facilitate the development of 3D mapping of the river bank environment and accurate measurement of key environmental variables from an autonomous craft in-transit within the river environment.

Within this project, the methodology will be specifically aimed at co-locating fish (via individual implanted fish tags), river depth and water velocities (via Acoustic Doppler Current Profiler) from a moving on-water sensor platform Dr. Rivas Casado.

The research is sponsored by Magellium Ltd and the Environment Agency. Project outputs will be used to develop industrially focused technologies (Magellium) and inform the future environmental sensing requirements of the national environment regulator (Environment Agency).

The project links to current EPSRC work on ADCP technology for fish passage assessment carried out at Cranfield University under the supervision of Dr. Monica Rivas Casado and Dr. Andrew Gill.

Also Read  Masters by Research in English Studentship

The PhD will be based at Cranfield University with supervisory support in computer vision techniques from Dr. Toby Breckon, School of Engineering and Computer Science, Durham University.

Supervisors:
Dr. Monica Rivas Casado – Cranfield University E: m.rivas-casado@cranfield.ac.uk T: +44 1234 750111 x2706
Dr. Toby Breckon – Durham University

Co Supervisors:

Dr Andrew Gill – Cranfield University
Dr Kim Blackburn – Cranfield University

Entry Requirements

Applicants should have good background in any of computer science, artificial intelligence, electrical engineering or a related discipline with a strong programming ability in a high level language (preferably C/C++, Java or Matlab). Candidates should hold at least a 2:1 honours degree or equivalent in Computer Science, Electrical Engineering or a related discipline (Masters degree a plus). In addition applicants should have a good knowledge of mathematics (especially algebra, statistics and geometry), a desire to work in the field and an interest in aquatic environments/fish ecology. Prior experience in computer vision, image processing and/or machine learning is a plus although not essential.

Fees

*Supported by  Magellium Ltd, The Environment Agency and EPSRC, due to funding restrictions this studentship will cover the tuition fees at the UK/EU rate only and provide a bursary of up to £15,500  p.a for three and a half years

For full eligibility visit the EPSRC website

How to apply

For initial enquiries please contact Dr. Monica Rivas Casado m.rivas-casado@cranfield.ac.uk  

If you are eligible to apply for this research studentship, please complete the online application by clicking the Apply link below.

Please specify project title on the application form.
Applications are not accepted by email.
Early applications are encouraged.

Also Read  Temporary Researcher Post

For further information contact us today:
School of Applied Sciences
T: +44 (0)1234 754086
E: appliedsciences@cranfield.ac.uk

Leave a Reply

Your email address will not be published. Required fields are marked *