[robocup-worldwide] PhD studentship in Self-Motivated Learning for Robots at U. Hertfordshire

[Daniel Polani]

			Research Studentship

		     University of Hertfordshire
	      Science and Technology Research Institute

Applications are invited from candidates for a PhD studentship on

	 Information-Driven Self-Motivated Learning in Robots

The studentship will aim to extend a promising novel class of
self-motivated learning and behaviour models for robots. It is based
on a set of recently developed information-theoretic learning
techniques and models. The project will involve the development and
implementation of such techniques to identify desirable robot
behaviours in a way intrinsic to the robot, to acquire them
incrementally acquisition, to refine and expand them, triggered by
need. We expect the deployment and application of these novel
techniques in both simulation as well as hardware robot scenarios,
specifically competitive scenarios and scenarios with scalable
complexity.

The prospective candidates should have a keen interest in developing
novel learning and skill acquisition techniques for robots, and very
strong programming skills (also ideally experience in scripting and
robot control) as well as a computational background from a relevant
area such as Computer Science or Engineering, Physics, Mathematics,
Statistics or another relevant discipline. A good
mathematical/numerical background would be desirable, ideally
including probability theory and data modelling/neural network
techniques, as well as general machine learning and bio-inpired AI
techniques.

Successful candidates may be eligible for a research studentship award
from the University (equivalent to GBP 12,940 per annum bursary plus
the payment of the standard UK student fees).

The envisaged research will take place in the vibrant and enthusiastic
research environment of the Adaptive Systems Research Group in the
School of Computer Science (Faculty of Engineering and Information
Sciences) at the University of Hertfordshire, UK. The university is
located in Hatfield, less than 25 minutes by train from London Kings
Cross station, one hour from Cambridge, with convenient access to
Stansted, Heathrow and Luton airports and not far from the historic
town of St. Albans.

Contact for informal inquiries on the research topic: Dr. Daniel
Polani (E-mail: d.polani at herts.ac.uk)

For further information on the application process and an application
form, contact

  Mrs Lorraine Nicholls 
  Research Student Administrator
  STRI, Faculty of Engineering and Information Sciences
  University of Hertfordshire
  College Lane, Hatfield, Herts, AL10 9AB, UK.  

  Tel: 01707 286083 
  Fax: 01707 284185 

or email:

  L.Nicholls at herts.ac.uk

The short-listing process will begin on 25th July 2008, but earlier
application is encouraged.