PhD studentship in Machine Learning and Artificial Intelligence (AI) Systems: Distributed Deep Learning, Personalising Foundation Models and Building Efficient Autonomous Distributed AI. Sep 24 start.


   School of Informatics

   Tuesday, June 18, 2024  Funded PhD Project (Students Worldwide)

About the Project

Machine Learning and Artificial Intelligence (AI) Systems

Please contact Amos Storkey () as soon as possible about this opportunity.

One fully funded Machine Learning PhD position to work with Prof Amos Storkey in the School of Informatics at the University of Edinburgh, on a project titled “Machine Learning and Artificial Intelligence (AI) Systems: Distributed Deep Learning, Personalising Foundation Models and building Efficient Autonomous Distributed AI”. The student will be part of the Bayesian and Neural Systems Group

This project looks at advancing state of the art in current methods in Machine Learning, especially Deep Learning, Reinforcement Learning and Artificial Intelligence (AI) by making AI methods more efficient, and making learning capability more autonomous and distributed. This leads to integration and communication between different independent machine learning and AI systems. This is suited to both computer science/engineering oriented students and maths/physics students looking at the foundational mathematics for machine learning, or mathematical and probabilistic AI. The potential application areas vary from computer vision to natural language processing.

E.g. When we build AI tools using Machine Learning to e.g. plan for the traffic for an event, it is affected by other distributed information - weather may affect the demand for the event, time of day may affect the interaction with work commute patterns etc. A separate AI tool to predict e.g. the effects of different ticket pricing mechanisms for the event will depend on much the same information - it would be good for the AI tools to integrate. But how can they? The same follows in computer vision - activity at one location or sensor interacts with other cameras or sensors in geographically related locations. Integrating computer vision information from different sensors is vital, even if those sensors are deployed as mobile edge devices.

The researcher on this project will spend time pioneering new machine learning, AI and deep learning methods to make modern machine learning models, foundation models and generative AI techniques more efficient effective and distributed. We want methods to no longer aggregate towards a small number of large players in the market. We want to democratize AI.

Candidate’s profile

  • a strong degree or higher qualification in a relevant field (e.g. artificial intelligence, machine learning, computer science, maths/mathematics, engineering, physical sciences, economics or any other field where evidence is provided of sufficient computing and mathematical background)
  • solid experience of programming, learning methods and ideally deep learning environments (e.g. pytorch) or a computer systems background
  • preferably, good mathematical skills and an understanding of either computer systems architecture or economic systems
  • demonstrable writing capability.

Studentship and eligibility

This funded post is suitable for a home student (e.g. students ordinarily resident in Scotland or the rest of the UK – England, Wales or Northern Ireland, Republic of Ireland, and EU-EEA nationals with Pre/Settled status). Overseas students can be considered for competitive funding.

Application information

We advise eligible and potentially interested students to contact  (), Professor of Machine Learning and Artificial Intelligence (AI) as soon as possible with a CV and statement of research interest for more information, and an informal discussion of the PhD position.

For more information please visit: PhD studentship in "Machine Learning Systems: Towards methods for community-integrated autonomous federated AI agents" | The University of Edinburgh.

Environment

The School of Informatics is one of the largest in Europe and currently the top Informatics institute in the UK for research power, with 40% of its research outputs considered world-leading (top grade), and almost 50% considered top grade for societal impact. The University of Edinburgh is constantly ranked among the world’s top universities and is a highly international environment with several centres of excellence. It has been researching Artificial Intelligence (AI) for over 60 years, and has pioneered many key machine learning methods. It has great strengths in computer vision and natural language processing.

Computer Science (8) Economics (10)

Funding Notes

This funded post is suitable for a home student (e.g. students ordinarily resident in Scotland or the rest of the UK – England, Wales or Northern Ireland, Republic of Ireland, and EU-EEA nationals with Pre/Settled status), EEA student, or students from Japan, Australia, New Zealand, US, Canada. Please be aware that queries not fitting this will not receive a response. Sep 24 start.


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