Sort by
Refine Your Search
-
Listed
-
Employer
- University of Oxford
- DURHAM UNIVERSITY
- Durham University
- King's College London
- AALTO UNIVERSITY
- University of Oxford;
- Durham University;
- Heriot Watt University
- Queen Mary University of London
- Queen Mary University of London;
- University of Lincoln
- University of Liverpool
- University of London
- 3 more »
- « less
-
Field
-
NSF-EPSRC project “DMS-EPSRC: Asymptotic Analysis of Online Training Algorithms in Machine Learning: Recurrent, Graphical, and Deep Neural Networks”. The research will involve collaboration with
-
(http://ori.ox.ac.uk/labs/goals/) within the Oxford Robotics Institute (ORI), as part of the EPSRC Programme Grant in Embodied Intelligence (https://embodiedintelligence.web.ox.ac.uk) and other follow
-
demonstrations. The successful candidate will work at the intersection of multi-disciplinary modelling, advanced AI algorithms, and decision-support tool development. Responsibilities will include programming
-
of Computer Science. The post-holder will report directly to Professor Paul Goldberg and will work on the EPSRC-funded project "Driving Behaviour in Multi-winner Voting" within the Algorithms and Complexity Theory
-
We are looking for a Postdoctoral Researcher in Computational Game Theory, including Social Choice Theory at the Department of Computer Science. The post-holder will report directly to Professor
-
Research Assistant or Postdoctoral Research Associate About the Role The School of Electronic Engineering and Computer Science at Queen Mary University of London seeks to recruit a Research
-
About us The Department of Informatics is looking to recruit a Postdoctoral Research Associate to work on data mining, in the context of a project funded by Leverhulme Trust, in the Department
-
demonstrations. The successful candidate will work at the intersection of multi-disciplinary modelling, advanced AI algorithms, and decision-support tool development. Responsibilities will include programming
-
deep neural networks to guide the development of algorithmic paradigms aimed at combining statistical optimality with computational efficiency. Reinforcement Learning through Stochastic Control. We will
-
will also investigate process optimisation algorithms, providing a route toward autonomous optimisation and ultimately enabling long term stable operation under variable load conditions. This post is