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Job summary

Job ID
Posting Date
University of Southampton
Job type
Full time
30,688.00 - 30,688.00  per year
Hours of Work
Fixed term contract
Job reference code

University of Southampton

Research Fellow in Swarm Robotics

Job description

Location:  Highfield Campus
Salary:   £30,688 Per annum
Full Time Fixed Term - 2 years
Closing Date:   Friday 11 May 2018
Interview Date:   To be confirmed
Reference:  997118FP

The University of Southampton currently has an excellent opportunity for a research fellow at its School of Electronics and Computer Science. 

Ranked in the top one percent of universities globally, the University of Southampton has an international reputation for its research, teaching and enterprise activities. Electronics and Computer Science is the leading department of its kind in the UK, with an established track record for world-leading research in computer science, electronics, and electrical engineering. At the last Research Excellence Framework, Electronics and Computer Science was first in the UK for the volume and quality of research in Electrical and Electronic Engineering. The volume and quality of Computer Science research is in the top 10 in the UK, with 100% of Computer Science research impact rated as world-leading or internationally excellent.

Applications are invited for a Research Fellow in robotics at the Agents, Interaction and Complexity Group. You will be working on an interdisciplinary project that is seeking to develop algorithms for resilient robot swarms, capable of rapidly -- in no more than a few minutes -- recovering from faults and damages sustained by individual robots of the swarm. This is to be achieved by developing a novel family of algorithms to (i) creatively discover a large and diverse map of swarm robot behaviours, and (ii) when damaged, efficiently select compensatory behaviours from the map via trial-and-error reset-free learning. Through close collaboration with academic and industry project partners, this research will ultimately lead to the next generation of robot swarms, capable of sustained operation for extended periods of time without human intervention. The developed algorithms will be demonstrated on, (i) wheeled mobile robot, and (ii) aquatic surface drone swarms.

The posts will be based in the Agents, Interaction and Complexity (AIC) research group ( You will be working with Danesh Tarapore and will be joining an internationally renowned team applying techniques from machine learning, evolutionary computation, swarm robotics, multi-agent systems, and autonomous systems to a range of complex real-world problems.

You should possess a PhD* in a relevant discipline (Computer Science, Engineering, Robotics, Artificial Intelligence, Machine Learning or a closely related discipline), or equivalent professional qualification and experience, have established a strong research pedigree in your area (as evidenced by publications in top quality journals and conferences) and excellent coding, statistical and data analysis skills. In particular, expertise in one or more of the following areas will be an advantage: evolutionary computation and/or machine learning. Furthermore, you should have a strong interest in the application of these techniques in swarm robotic systems. 

The posts will be for two years, starting in August 2018. Informal inquiries may be made to Dr. Danesh Tarapore.

*Applications for Research Fellow positions will be considered from candidates who are working towards or nearing completion of a relevant PhD qualification. The title of Research Fellow will be applied upon successful completion of the PhD. Prior to the qualification being awarded the title of Senior Research Assistant will be given.

Application procedure:

You should submit your completed online application form on our website. The application deadline will be midnight on the closing date stated above. If you need any assistance, please call Rosie McPhail (Recruitment Team) on +44 (0) 23 8059 4043. Please quote reference 997118FP on all correspondence. References are requested along with your application. This reference system is automated so please ensure you provide the correct email address and allow time for these to be received, prior to the close date, to assist the department with shortlisting.

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