SCHOOL OF ENGINEERING AND APPLIED SCIENCE
EPSRC Industrial Mathematics CASE PhD Studentship (3 years)
Topographic Information Visualisation
Applications are invited for a three year PhD studentship, supported by the Engineering and Physical
Sciences Research Council (EPSRC) through the Knowledge Transfer Network for Industrial
Mathematics to be undertaken within the Nonlinearity and Complexity Research Group
(www.ncrg.aston.ac.uk) at Aston University. The successful applicant will join an international
research group working on advancing knowledge in nonlinear and dynamic statistical pattern
processing. The studentship is offered in collaboration with Thales Underwater Systems Limited.
The position is available to start in October 2011 (subject to negotiation).
Financial Support
Financial support will be provided to Home/EU students (subject to eligibility) at the standard
EPSRC rate with the corresponding standard EPSRC increases in subsequent years, plus a £3,000
per year award from the collaborating company.
Background of the Project
This project focuses on the mathematical problem of the relative dissimilarity representation of
signals, driven by the real-world sonar array problem domain, and specifically aimed at massive data
reduction whilst retaining informative content for the human operators. In response to the
requirement for human decision support aids to reduce information overload and so to represent high
dimensional structured data (data with interpoint relative similarity measures), this project aims to
research prototype topographic visualisation models and compare and contrast with other state of the
art models, and develop extended versions using models for uncertainty in data, structures and
knowledge appropriate to the sonar sensor array domain. In addition, the project will explore the
development of new types of data analysis and representation based on the dissimilarity
representation. Nonlinearity and uncertainty in data and parameters and models will be included
which will modify the visualisation space distributions. Dynamics and nonstationarity of the signal
domain will be also be incorporated through feature extraction and adaptive models.
Person Specification
The successful applicant should have a first class or upper second class honours degree or equivalent
qualification in applied or computational mathematics, physics, mathematically-oriented
engineering. Preferred skill requirements include knowledge/experience of signal processing and/or
data analysis. Applicants should fulfil the eligibility criteria for EPSRC funding through UK
nationality and/or residency status (see http:www.epsrc.ac.uk/).
For informal enquiries about this and other opportunities within the Nonlinearity and Complexity
Research Group, contact Professor David Lowe by email ([email protected]).
Application forms, reference forms and details of entry requirements, including English language are
available at http://www1.aston.ac.uk/eas/research/prospective-research-students/how-to-apply/
Please send your completed application form with at least two academic references and a full CV to
Susan Doughty, Research Admissions, School of Engineering and Applied Science, Aston
University, Aston Triangle, Birmingham B4 7ET, UK.
Closing Date: August 15th 2011.