Job profile

Research Fellow – School of Computing

Full time – Fixed term contract – 42 months

Who we are

It's an exciting time to join us! We are an ambitious university, operating at the leading edge of our academic disciplines in research, pedagogy and professional practice. We are looking for passionate and ambitious academic staff to deliver innovative, research-led teaching programmes.

Our School of Computing is home to 70 academics, 1400 students and holds professional accreditation from the British Computer Society, with some of the most impressive computing lab facilities in the UK.

The Role

We are seeking a Research Fellow to work on a 42 month EPSRC funded project “Keep Learning” that will develop an optimisation system for solving combinatorial and constrained problems. The system "keeps- learning" in response to a continual instance-stream, rapidly producing optimised solutions to instances and situations that go beyond those envisaged at initial design.

The novelty of the project is in integrating approaches from meta-heuristic search  and constrained optimisation with machine-learning techniques for instance-prediction and algorithm-selection.  The post is part of a joint research project in collaboration with the University of St Andrews.

The role holder will conduct research under the supervision of senior colleagues to design, implement and evaluate novel machine-learning and evolutionary mechanisms that (1) predict future characteristics of instances based on past history (2) generate new instances based on predicted features (3) apply meta-heuristic methods to generate new solvers (4) implement algorithm-selection methods (5) implement novel methods to enable continual adaptation of the system based on past experiences.

Although based at Edinburgh Napier University, the role holder will be expected to work closely with a fellow researcher at  the University of St Andrews, including spending short periods of time at this institution.

The research fellow will be expected to identify opportunities for research publications and contribute as a lead author, as well as to help with organisation of related workshops/meetings. Edinburgh Napier is fully committed to supporting researcher training and career development, including mentoring, as a signatory to the Concordat for Career Development of Researchers.

What are we looking for

Essential requirements:

• A PhD in a relevant research area such as meta-heuristic optimisation, self-adapting systems, machine-learning or equivalent relevant demonstrable research experience.
• Demonstrable experience of conducting research in the field of optimisation
• Demonstrable experience and/or good knowledge of meta-heuristic search algorithms
• Demonstrable experience and/or good knowledge of machine-learning methods for prediction
• Working in a team to deliver research
• A strong publication track-record demonstrating ability to write up research work for high-profile publications

Desirable requirements:

• Experience of working with algorithm or heuristic generation methods such as Genetic Programming
• Experience or knowledge of machine-learning techniques for prediction, including feature-selection methods, particularly in relation to time-series data
• Knowledge of constraint-based optimisation methods, including exact solvers
• Very good programming skills, e.g. in Python, Java or C++, including experience of standard machine-learning libraries

Please see the full job description here

Benefits we offer

In return, we offer a great working environment where we support ambition, recognise achievement and offer an attractive benefit package. This includes a generous pension scheme, professional development opportunities, discounted access to onsite sports facilities and a wide range of other staff discounts.

Salary: Grade 5, £32,816 - £39,152 per annum

Additional Information

Closing date: 1^st April (midnight GMT)

Interviews: 12^th April (online)

The University is committed to inclusion, demonstrated through our work in respect of our diversity awards and accreditations and holds Disability Confident, Carer Positive and Stonewall Scotland Diversity Champion status.  More details can be found here.