Research Associate - #1203125

Edinburgh

£39,347 to £46,974
per annum (Grade 7)

Full Time

Fixed-Term/Contract

25th June 2024

23rd July 2024

10792

Fixed term contract - Temporary until 31st August 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 successful candidate will be directly working with Amos Storkey (Principle Investigator) in the School of Informatics, and Elliot Crowley (co investigator) in the School of Engineering. The post will be based in Informatics.

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.

The University of Edinburgh component of the Horizon project dAIEdge is led by Amos Storkey (Informatics) and Elliot J. Crowley (Engineering) and involves many other academic institutions and key companies across Europe. The successful candidate will be based in the Informatics Forum, in central Edinburgh.

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 (Desirable).


• 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 (Desirable).


• 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.