Ph.D. Studentship
Applications are invited for a PhD studentship, available within the Digital
Imaging Research Centre, Faculty of Computing, Information Systems and
Mathematics at Kingston University. The studentship is fully funded by the
The Leverhulme Trust (www.leverhulme.ac.uk <http://www.leverhulme.ac.uk> ).
Deadline for application form: 31st March 2009, expected start date 1st June
2009.
Stipend: 16.000 GBP p.a.
Machine and Statistical Learning for Herbarium Specimen Image Data Analysis,
Morphometrics and Classification
This multidisciplinary project is a collaboration with the University of
Surrey and The Royal Botanic Gardens, Kew (RBG). It builds on the growing
resource of high-resolution digitized images of specimens at the RBG.
Existing botanical morphometric studies have involved substantial prior
additional preparation of source material and much manual intervention in
the image processing. The main aim is to design algorithms to automatically
extract and analyse morphological measurements (morphometric features) from
digital images of complete specimens. These algorithms will exploit
innovative computational methods to automate the image analysis. They will
be used in comparative studies of plant diversity and in developing an
automated, web-based identification system.
The successful Ph.D. student will be engaged in pursuing two main
task-oriented research objectives:
· Measurement: Using image processing techniques to perform automatic
extraction of mathematically rigorous leaf character states from high
resolution images of good quality specimens to contribute significantly to a
better statistical understanding of leaf variation patterns.
· Modelling and Classification: using Machine Learning and Statistical
learning methods to create multidimensional leaf-based classification
models,
This Ph.D. studentship is a great opportunity to work on a multidisciplinary
project, in collaboration with computer vision researchers and biologists.
It will enable the student to combine image processing, statistics and
machine learning methods to develop scientifically and biologically sound
algorithms. The successful candidate should have a good degree in a
technical subject area, such as Computer Science, Engineering, Mathematics
or Physics. Furthermore, the candidate should have an interest in image
processing. We are looking for applicants with excellent programming skills
and a strong mathematical and statistical background.
For further details please contact Dr Paolo Remagnino
([email protected]), of the Digital Imaging Research Centre,
Kingston University, U.K.
Applying for the Studentship: You can download the application form from:
http://www.kingston.ac.uk/postgraduate/apply-now/documents/ku_postgrad_appli
cation_and_reference_form.pdf
Please return the completed application form together with an academic CV,
TWO references, academic certificates and any other documentation to:
Mrs B Tang
Research and Enterprise Officer
Kingston University, Faculty of Computing, Information Systems and
Mathematics
Sopwith Building, Penrhyn Road
Kingston upon Thames, Surrey, KT1 2EE, UK
e-mail: [email protected]
DD: +44 (0)20 8417 2054
Please assume that your application has not been successful if you have not
heard from us 4 weeks after the closing date. Please ensure that all
required documents are submitted together with your application as we are
unable to consider uncompleted application
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