Topographic Information Visualisation
Applications are invited for a full 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 Non-linearity and Complexity Research
Group at Aston
University. The successful applicant
will join an international research group working on state-of-the-art information analysis in
nonlinear and dynamic statistical pattern processing. The studentship is offered in collaboration
with Thales Underwater Systems Limited.
The position is available to start immediately (subject to
negotiation).
Financial Support
Financial support will be
provided to Home/EU students (subject to eligibility) at the standard EPSRC
rate (£13,590 for 2011/12) with the corresponding standard EPSRC increases in
subsequent years, plus a £3,000 per year award from the collaborating company (i.e. £16,590 p.a.).
Background of the Project
Visual
Informatics is a relatively recent and important area of research in
information analysis. This project will explore radically new ways to process
and visualise complex high dimensional information to present to human
operators. The motivation for the research is how to condense the immense
amounts of data in modern sonar arrays to remove noise, to locate and identify
objects and structures underwater, and to do so through time, but doing it in
such a way that a human can then interpret the resulting representation of
knowledge.
This
research has a wide application potential, especially in problems relying on
measuring multiple time series as it is breaking new ground in generic
information representation.
We will be
exploring prototype topographic visualisation models compared with other
state-of-the-art models, and exploring uncertainty in data, structures and
knowledge appropriate to the sonar sensor array domain. In addition, the project
will be developing new types of data analysis and representation based on the
dissimilarity representation. Dealing with dynamics, nonlinearity,
nonstationarity and uncertainty in data
and parameters and models will be a central aspect of this research.
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, or 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 www.epsrc.ac.uk).
For informal enquiries about
this and other opportunities within the Non-linearity and Complexity Research
Group, contact Professor David Lowe by email.
The online application form, 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/
Closing Date: 20th February 2012.
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