PhD Studentship: Evolution of learning and plastic neural networks for perception and control (focus on neuromodulation)

Application details:
Reference number: AS/CO-DARPA/2018/2
Start date of studentship: 1st October 2018
Closing date of advert: 2nd September 2018

A funded PhD position is available at the Computer Science Department, School of Science, Loughborough University, UK, on the topic of the evolution of lifelong learning in neural networks.

Research
The aim is to develop new neuroevolution algorithms for lifelong learning. The objectives are to devise machine learning systems that autonomously adapt to changing conditions such as variation of the data distribution, variation of the problem domain or parameters, with minimal human intervention. The approach will use neuroevolution, neuromodulation, and other methodologies to continuously discover and update learning strategies, implement selective plasticity, and achieve continual learning.

For an overview of the research direction, see the paper: Born to Learn: the Inspiration, Progress and Future of Evolved Plastic Artificial Neural Networks https://www.researchgate.net/publication/315710249_Born_to_Learn_the_Inspiration_Progress_and_Future_of_Evolved_Plastic_Artificial_Neural_Networks

Application areas include a variety of automation and machine learning problems, e.g. vision, control, and robotics, with a particular focus on resilience and autonomy.

Loughborough University is a top-ten rated university in England for research intensity (REF2014). In choosing Loughborough for your research, you’ll work alongside academics who are leaders in their field. You will benefit from comprehensive support and guidance from our Doctoral College, including tailored careers advice, to help you succeed in your research and future career.
Find out more: http://www.lboro.ac.uk/study/postgraduate/supporting-you/research/

Working environment. The successful applicant, based at the Computer Science Department, will work in an international team with opportunities for collaboration and travel. They will have access to a number of robotic platforms such as mobile and flying robots, manufacturing robots, High Performance Computing clusters, and GPU computing. The Computer Science Department and robotics laboratories have ongoing collaborations with large industries and programs to promote start-ups.

Entry requirements
The ideal candidate holds (or is about to obtain) at least a 2:1 honours undergraduate/postgraduate degree (or equivalent) in Computer Science, Mathematics, Statistics, Electrical or Electronic Engineering, and authored publications in recognised conferences/journals would be welcomed. Independent working skills are valued as well as the capability of working in a team. Collegiality and interpersonal skills are essential. Excellent English language skills are also essential (see requirements here http://www.lboro.ac.uk/international/englang/index.htm)

Contact details
Name: Andrea Soltoggio
Email address: [Email Address Removed]

How to apply
All applications should be made online at http://www.lboro.ac.uk/study/apply/research/. Under programme name, select Computer Science.

Please quote reference number: AS/CO-DARPA/2018/2