Job number: ACAD102930
Division/School: Academic Faculties
Contract type: Open ended contract staff
Working pattern: Full time
Salary: £32,548 to £41,212 per annum
Based in a world leading research team composed of members of the Visual Information Lab (VI-Lab) and the Applied Nonlinear Mathematics (ANM) Group within the School of Computer Science, Electrical and Electronic Engineering and Engineering Mathematics (SCEEM) at the University of Bristol this is an exciting opportunity to join a strong team developing state of the art mathematical models of the sea surface and their validation using SAR image analysis.
You will develop new models for the sea surface conditions, with a view to detect and characterise ship wakes. In order to validate the models, advanced methods for enhancing SAR image quality and for information extraction will be developed. The system will comprise a pipeline for processing data in a closed-loop with algorithms aiming at detecting ship wakes, followed by adaptation of the wake model. This will presuppose pre-processing of SAR data for enhancing image quality (despeckling, fusion and super-resolution), segmentation, and classification of the remote sensing imagery.
The two available positions will focus on the development of novel algorithms and associated software tools for the mathematical and statistical characterization of the sea surface and on the solving of a range of inverse problems involving SAR imagery, respectively. This will be achieved through a combination of sparse methodologies and modern optimization algorithms. You will report results internally and to industrial partners.
You will have a first degree and PhD (or equivalent level qualifications) in Mathematics, Electrical and Electronic Engineering or Computer Science (or closely related discipline) and have proven experience of image processing and analysis techniques as well as programming using Matlab and/or C++.
This post is offered on a full time, open ended basis with funding available for 3 years.
Informal enquiries can be made to: Dr Alin Achim (email@example.com; +44 (0) 117 331 5137)
Closing date for applications: 12-Nov-2017.
It is anticipated that interviews will take place shortly after the closing date.
The University is committed to creating and sustaining a fully inclusive culture. We welcome applicants from all backgrounds and communities.
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