Research Associate

Full Time- 35 hours per week

Fixed Term- 12 months 

The Opportunity:

The School of Informatics, University of Edinburgh invites applications for a research associate position in the general area of data-driven networking.

The successful candidate will contribute to industrially funded projects that are broadly aimed at developing/evaluating methods and systems for enabling data-driven networks. You will be expected to lead the research on certain aspects of these projects while contributing to other aspects, including assisting with research student supervision, preparing presentations and reports for deliverables and developing related/follow-on projects. Candidates must have a PhD (or nearing completion) in Computer Science or related field. Evidence of strong research experience as demonstrated through publications at top-tier conferences or high-impact journals is essential. We are looking for a highly motivated candidate with strong initiative and commitment to excellence, and an ability to conduct world-class research in a team setting.

This post is advertised as full-time (35 hours per week), however, we are open to considering part-time or flexible working patterns. We are also open to considering requests for hybrid working (on a non-contractual basis) that combines a mix of remote and regular on-campus working. 

Please include the following documents in your application:

• CV
• Cover letter

For informal queries please contact: Prof. Mahesh Marina (mahesh@ed.ac.uk)

Your skills and attributes for success:

• PhD (or near completion) in Computer Science or related field

The following criteria are not yes/no factors, but questions of degree. Recruitment will aim at selecting those candidates with the best possible performance in all these criteria.

• Excellent research track record as demonstrated through publications at top-tier conferences or high-impact journals.
• Strong experience of research in one or more of the following areas: Data-driven network monitoring, automation and optimization methods; Cloud service assurance; Traffic engineering; Software-defined networking; Wireless and mobile networking; Deep learning; Network data analysis and modelling; Synthetic data generation; Networked systems design and experimental evaluation; O-RAN architecture and use cases; Edge computing; Network measurement; Network security.
• Ability to communicate complex information clearly, orally and in writing.
• Possess high level of initiative, be detail oriented and ability to effectively work in a team setting.
• Preferably, experience in research student supervision and grant writing.

Advert information