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1 Research associate and 2 funded PhD. positions on the evolution of neural learning and plasticity

One research associate and two funded Ph.D. positions are available at the Computer Science Department, School of Science, Loughborough University, UK, on the topics 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.


Working environment. The research associate and Ph.D. students, 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.

Loughborough University is ranked 7th in the UK in the 2019 League Table Ranking  http://www.thecompleteuniversityguide.co.uk/loughborough/performance ), and is located in Loughborough, a town well connected to London by a 1h20m journey by train.


Requirements.

Postdoc: A Ph.D. in Computer Science or related with a strong publication record, coding abilities, predisposition to work in a team and independence, passion for science, solid work ethics.

Ph.D. students: The ideal candidate holds (or is about to obtain) a first-class honour undergraduate/postgraduate degree (or equivalent) in Computer Science, Mathematics, Statistics, Electrical or Electronic Engineering, or has authored publications in recognised conferences/journals. 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)


Period and salaries. 

Postdoc position: until June 2020 (with possible extension) with a competitive salary at Grade 6 (http://www.lboro.ac.uk/services/hr/benefits/pay-rewards/)

Start: as soon as possible.

Ph.D. studentships:

Scholarship: £14,777 per annum plus tuition fees at the UK/EU rate.

Start: August 2018 or shortly after.

Duration: 3 years.

 

Enquiries and applications. Interested candidates are invited to send preliminary enquiries to a.soltoggio@lboro.ac.uk including a CV, a university transcript of marks, a list of references, and a statement of about 300 words motivating their interest in this area of research.

Fully funded PhD position in Neural Learning / Robotics / Evolutionary Neural Networks

A fully funded PhD position is available at the Computer Science Department, School of Science, Loughborough University, UK, on the topics of Neural Learning / Robotics / Evolutionary Neural Networks.

Loughborough University is ranked 11th in the 2016 UK League Table Ranking (http://www.thecompleteuniversityguide.co.uk/loughborough/performance , and is located in Loughborough, a town well connected to London by a 1h20m journey by train.

Research.The focus is on developing new neural learning algorithms with possible applications to a variety of automation and machine learning problems, e.g. vision, robotics, autonomous vehicles, manufacturing technology. We seek an outstanding candidate, capable of defining their own research project and bringing novel ideas and initiatives to the lab.

Working environment. The student, based at the Computer Science Department, School of Science, will have access to a number of robotic platforms, from humanoid robots, to UAVs and a number of industrial and service robots, as well as a High Performance Computing cluster and GPUs. Research is conducted with the Intelligent Interactive System Division in the department of Computer Science, but also within the cross-department interest group on Deep Automation, Learning and Evolution. The group has access to laboratories across campus including the Intelligent Automation Lab (Mechanical and Manufacturing Engineering), research groups in Aeronautical and Automotive Engineering, and the Centre for Information Management. The department collaborates with leading national and international industrial partners.

Requirements. The ideal candidate holds (or is about to obtain) a first-class honour undergraduate/postgraduate degree (or equivalent) in Computer Science, Mathematics, Statistics, Electrical or Electronic Engineering, or has authored publications in recognised conferences/journals. 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 highly desired (see requirements here http://www.lboro.ac.uk/international/englang/index.htm)

Period/Scholarship.

Start: October 2015.
Duration: 3 years.
Scholarship: £14,057 per annum plus tuition fees at the UK/EU rate (currently £4,052 p.a.)
Application deadline: 12 July.

Enquiries and applications. Interested candidates are invited to establish a preliminary contact with me (a.soltoggio@lboro.ac.uk), possibly including a CV, the names and addresses of two referees, and a statement of research interest (maximum 300 words), before submitting the full application at http://www.lboro.ac.uk/study/apply/research/