Research Fellow – School of Computing

Edinburgh, City of Edinburgh (GB)
£33,309 - £ 39,739 per annum
28 Jun 2022
End of advertisement period
31 Jul 2022
Contract Type
Fixed Term
Full Time

Job title: Research Fellow – School of Computing, Full time – Fixed term

Job reference: 0000016242

Date posted: 27/06/2022

Application closing date: 31/07/2022

Salary: Grade 5, £33,309 - £ 39,739 per annum

Package: Excellent Benefits Package

Contractual hours: 35

Basis: Full Time

Job description

Research Fellow – School of Computing, Full time – Fixed term contract – 28 months

Who we are

The Nature-Inspired Intelligent Systems group sits within the School of Computing at Edinburgh Napier University in Scotland. The group conducts research in a broad range of topics that include meta-heuristic optimisation, evolutionary robotics, multi-agent systems, machine-learning, reinforcement learning and natural language generation.

The Role

Prof. Emma Hart is seeking a Research Fellow to work on an EPSRC funded project “Keep Learning” that will develop an optimisation system for solving combinatorial and constrained problems. The goal is to develop a system that "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 (e.g. in continual learning and multi-domain learning) 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 Prof. Emma Hart and in collaboration with the postdoc based in St Andrews to design, implement and evaluate novel machine-learning and evolutionary mechanisms that for example (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) enable algorithm-selection (5) enable continual adaptation and improvement 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, situated approximately 1.5 hours by public transport from Edinburgh, including spending short periods of time at this institution (e.g.one or two weeks per year with costs covered by the project).

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.

For overview of project from the funder can be reviewed here.

What are we looking for:

For detailed role description, please click here:

Essential requirements:

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

Desirable requirements:

  • Experience of working with algorithm/heuristic generation methods such as Genetic Programming
  • Experience or knowledge of machine-learning techniques, including feature-selection methods (particularly in relation to time-series data), or in continual learning or multi-domain learning
  • Knowledge of constraint-based optimisation methods, including exact solvers
  • Experience of using standard machine-learning libraries

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, £33,309 - £ 39,739 per annum

Additional Information

Closing date: 31st July @11:59 pm

Interviews: TBC, week commencing 8th August

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.