Research Fellow in Bio-Inspired Artificial Intelligence and Robotics Ref: 2091
School/department: School of Engineering and Informatics, Department of Informatics
Hours: Full time. The position will include extended trips to Australia (1-6 months/visit, and approximately 12 months in total over the 3 years)
Contract: Fixed term for 3 years
Salary: Starting at £33,199 and rising to £39,609 per annum
Placed on: 12 August 2019
Closing date: 23 September 2019. Applications must be received by midnight of the closing date.
Expected interview date: 7 October 2019
Expected start date: 1 November 2019
Are you a talented and ambitious computer scientist, computational neuroscientist or machine learner? Are you looking for an opportunity to use cutting edge technology to gain new understanding of how small-brained insects learn so rapidly and robustly, and in turn develop novel active AI algorithms that are inspired by these insights? We have an opportunity for a Research Fellow to join the Brains on Board team at the Department of Informatics at the University of Sussex. The Fellow will additionally work in close collaboration with a partner Research Fellow at the University of Sheffield and world-leading neuroscientists in Australia. The project is funded through the prestigious £1.2m EPSRC International Centre to Centre Collaboration project: “ActiveAI: active learning and selective attention for rapid, robust and efficient AI.”
Your primary role will be to develop a new class of ActiveAI controllers for problems in which insects excel but deep learning methods struggle. These problems have one or more of the following characteristics: (i) learning must occur rapidly, (ii) learning samples are few or costly, (iii) computational resources are limited, and (iv) the learning problem changes over time. Insects deal with such complex tasks robustly despite limited computational power because learning is an active process emerging from the interaction of evolved brains, bodies and behaviours. Through a virtuous cycle of modelling and experiments, you will develop insect-inspired models, in which behavioural strategies and specialised sensors actively structure sensory input while selective attention drives learning to the most salient information.
The cycle of modelling and experiments will be achieved through extended visits to Australia, which will allow you to interact with biologists and shape novel insect experiments, that in turn will inspire computational and robotic models and novel algorithms. This includes significant scope for you to creatively shape and drive the project to your interests. In particular, you will be able to organise the length of these visits flexibly but it is anticipated you will spend approximately 12 months in total in Australia over the 3 years in visits of 2-6 months. In this way, we will both advance neuroscience and enable ActiveAI solutions which will be efficient in final network configuration, robust to real-world conditions and learn rapidly.
You will work under the supervision of Professors Andrew Philippides, Thomas Nowotny and Paul Graham within the Department of Informatics at Sussex and will join a team of 4 research fellows and 4 PhD students at Sussex. This is in addition to our collaborators in the Universities of Sheffield and Queen Mary within the £4.8m EPSRC Brains on Board Programme Grant. More specifically, you will be in partnership with a corresponding Research Fellow and team at the University of Sheffield, led by Dr Mike Mangan. Together, you will lead a new collaboration with world-leading research partners in Australia including Professor Andrew Barron at Macquarie University, Dr Bruno van Swinderen at the University of Queensland and Dr Karin Nordstrom at Flinders University through extended secondments.
You should be educated to PhD level (or be close to completion) in machine learning, autonomous robotics, artificial intelligence, computational neuroscience or a related discipline, with excellent modelling and analytic skills. You will ideally have some experience with neural networks (especially to model biological or time-varying systems), cross-disciplinary collaborations, computer vision or GPU computing, though candidates must have a desire to improve or acquire skills in these areas.
When applying, please fill in the application form and attach a full CV. Use the space for additional information in support of your application to address in detail what you are bringing to the project and why you are the best candidate for the position, making reference to the role specific criteria as outlined in the Job Description. For informal enquiries, please email Andy Philippides, Professor of Biorobotics at the University of Sussex (email@example.com).
How to apply
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