Research Associate

Grade UE07: £41,064 -  £48,822 per annum (pro-rata if part time)

CSE / School of Informatics

Full-time: 35 hours per week 

Fixed term: 12 months 

The Opportunity:

The successful candidate will contribute to an industry-funded project focused on using compilation techniques to improve the performance of inference over sparse neural networks. You will be expected to lead the research on certain aspects of the project while contributing to rest of the project (assisting in research student supervision, preparing presentations and reports for deliverables, developing related/follow-on projects). 

Candidates must have a PhD (or nearing completion) in Computer Science or related field and a strong research track record demonstrated through publications at top-tier venues. Experience with building systems for machine learning, performance tuning, and building optimizing compilers are highly desirable. 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, 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

Your skills and attributes for success:

• A PhD (or near completion of PhD) in Computer Science or related field. 
• Excellent research track record as demonstrated through publications at top-tier conferences and/or high-impact journals.
• Preferably, experience in building systems for machine learning.
• Preferably, experience in building optimizing compilers. 
• Ability to communicate complex information clearly, both orally and in writing.
• Possess high level of initiative, be detail oriented and ability to effectively work in a team setting.

Click to view a copy of the full job description (opens new browser tab)

As a valued member of our team you can expect:

• A competitive salary
• An exciting, positive, creative, challenging and rewarding place to work.
• To be part of a diverse and vibrant international community
• Comprehensive Staff Benefits, such as a generous holiday entitlement, a defined benefits pension scheme, staff discounts, family-friendly initiatives, and flexible work options. Check out the full list on our staff benefits page (opens in a new tab) and use our reward calculator to discover the total value of your pay and benefits

Championing equality, diversity and inclusion

The University of Edinburgh holds a Silver Athena SWAN award in recognition of our commitment to advance gender equality in higher education. We are members of the Race Equality Charter and we are also Stonewall Scotland Diversity Champions, actively promoting LGBT equality.

Prior to any employment commencing with the University you will be required to evidence your right to work in the UK. Further information is available on our right to work webpages (opens new browser tab).

The University may be able to sponsor the employment of international workers in this role.  This will depend on a number of factors specific to the successful applicant. Please note if the role is offered on a part-time basis, it may result in sponsorship being dependant on a number of factors specific to the successful applicant or the role no longer meeting the Home Office’s criteria for sponsorship.

Key dates to note                                                                                                          

The closing date for applications is 16 October 2025.

Unless stated otherwise the closing time for applications is 11:59pm GMT. If you are applying outside the UK the closing time on our adverts automatically adjusts to your browsers local time zone.

Feedback is only provided to interviewed candidates.

As a world-leading research-intensive University, we are here to address tomorrow’s greatest challenges. Between now and 2030 we will do that with a values-led approach to teaching, research and innovation, and through the strength of our relationships, both locally and globally.