Funded Ph.D. positions are available at the Computer Science Department, School of Science, Loughborough University, UK, on the topic of the evolution of lifelong learning in neural networks.
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
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 Graduate School, including tailored careers advice, to help you succeed in your research and future career.
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.
The Ph.D. students, based at the Computer Science Department, will work on a project funded by DARPA in an international team: see further details on the project and team at: http://www.hrl.com/news/2018/0
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/interna
The studentship is for 3 years and provides a tax-free stipend of £14,777 per annum for the duration of the studentship plus tuition fees at the UK/EU rate. International (non-EU) students may apply however the total value of the studentship will be used towards the cost of the International tuition fee in the first instance.
Name: Andrea Soltoggio
Email address: firstname.lastname@example.org
How to apply:
Interested candidates are invited to send preliminary inquiries to email@example.com including a CV, a list of references, and a statement of about 300 words motivating their interest in this area of research, in addition to submission of a University application form.
All applications should be made online at http://www.lboro.ac.uk/study/a
Please quote reference number: AS/CO-DARPA/2018