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PhD in robotic learning of periodic activities
A PhD position is available in our lab.
This project is part of an FP7 project called Strands (http://www.strands-project.eu/), involving 30+ people, of whom a team of 6 work at the Birmingham IRLab (http://www.cs.bham.ac.uk/research/groupings/robotics/). In the overall project we investigate the task a robot that must perform 4D mapping. By this we mean producing not just a map of space (3D mapping), but also of the activities that occur within that space. Such activity maps are necessary for robots to act within a space shared with humans.
The activities performed in an environment by many humans over a period of time can typically be viewed as being composed of many smaller complex events and interactions. Many of these events occur periodically. There are differences across repetitions. The challenge of this PhD is how to recognise and exploit this periodicity in order to build compact models of complex behaviour involving multiple humans over long timescales (hours and days). The work will consider how the ordering and frequency of sub-events can be learned, taking account of the fact that sometimes particular sub-events may not occur, or that their ordering may be changed.
The IRLab at Birmingham is a leading European lab working in many aspects of intelligent robotics. The group has five faculty, seven research fellows and fifteen research students. The lab has a state of the art equipment with access to a wide range of advanced platforms for mobility and manipulation.
You should have a Batchelors or Masters in Computer Science, Electronic Engineering, Mathematics or Physics. You should have excellent mathematical and coding skills. You will have graduated in the top 5% of your class.
In the first instance contact Jeremy Wyatt and Nick Hawes (jlw@cs.bham.ac.uk, nah@cs.bham.ac.uk), with your CV and transcript. Put “Strands Learning PhD application” in the subject line. Deadline for applications is the 30th June, late applications will be considered if the appointment process hasn’t gone too far.