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Research Associate: AI at the Edge?

The University of Edinburgh - Research Associate: AI at the Edge?

Location: Edinburgh
Salary: £37,099 to £44,263 Grade UE07, per annum (A revised salary range for this grade of £39,347 to £46,974 pa is planned to take effect from Spring 2024)
Hours: Full Time
Contract Type: Fixed-Term/Contract
Placed On: 26th January 2024
Closes: 1st March 2024
Job Ref: 9500

Fixed term to 31/08/2026

Full time (35 hours per week)

The School of Informatics at the University of Edinburgh is inviting applications for a Research Associate in Machine Learning and Artificial Intelligence with a particular focus on method development for Edge Devices, Scenarios and Environments. 

The Opportunity:

Machine Learning (ML) has a dramatic impact on our daily lives. The explosion in ML, however, is built on the back of the development of computer systems able to train and deploy ever more powerful models. 

Systems design fundamentally determines ML performance and capability. This is true for internet-scale ML and artificial intelligence (AI). Yet, more recently, it is especially evident in distributed, device-oriented, specialised and potentially mobile systems.  These more distributed “edge” settings provide many important challenges for the development of ML methods – methods must be able to be efficient, robust, online, adaptive, personalised, secure and private. This is the challenge this project addresses.

We seek candidates to join the dAIEdge project and network grant – working towards the development of machine learning and AI methods for edge devices. This would be suitable for machine learning or machine learning systems researchers in computer science, engineering, or from other disciplines.  The successful candidate will have a strong machine learning portfolio, and a knowledge of computer systems. The researcher will engage in cutting edge research in the field, and develop strong networking across Europe in the AI Edge arena.

This post is full-time (35 hours per week) and fixed term (grant ends 31st August 2026)

Your skills and attributes for success: 

  • PhD (or near completion) or equivalent research experience in artificial intelligence, machine learning methods, machine learning systems or a very related discipline.
  • Experience and evidence of effective independent research work within a research team, and contribution to the team effort. Evidence of ability to network and build collaborations.
  • Demonstrated quality of research performance, as evidenced by high-quality publications in top-tier machine learning/computer vision venues (e.g., ICML, NeurIPS, ICLR, AISTATS, UAI, AAAI, ACL, EMNLP, ICCV, ECCV, CVPR), and relevant journals (IEEE PAMI, JMLR among others).
  • Strong programming skills; experience with Python and deep learning libraries (e.g., PyTorch or TensorFlow).
  • Ability to communicate complex information clearly, orally and in writing, in English.

The following desirable criteria will be evaluated by the level of proficiency. Recruitment will aim at selecting those candidates with the best possible performance in these criteria.

Desirable knowledge, skills, and experience are:

  • Substantial previous research component in systems, on-device development, machine learning hardware or edge devices.
  • Broad knowledge of machine learning methods beyond modern deep learning methods. Knowledge of classical machine learning approaches and their foundations.
  • Understanding of multi-agent systems and game theory.
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