Sort by
Refine Your Search
-
Category
-
Program
-
Employer
- University of Sheffield
- ;
- UNIVERSITY OF SOUTHAMPTON
- ; The University of Manchester
- Cranfield University
- University of Bristol
- ; University of Birmingham
- ; University of Cambridge
- ; University of Sheffield
- ; University of Warwick
- ; University of York
- Aston University
- Heriot Watt University
- Imperial College London
- KINGS COLLEGE LONDON
- The University of Southampton
- UNIVERSITY OF SURREY
- University of Cambridge
- University of Glasgow
- University of Leicester
- University of Oxford
- University of Surrey
- University of the West of England
- 13 more »
- « less
-
Field
-
and its implementation in distributed systems. Main responsibilities: Research, develop, and optimise machine learning algorithms, including deep learning, for AV control and coordination. Apply multi
-
theoretical physics, whose responsibilities relate to distributed systems and the GPU optimization of AI algorithms. We expect the team to grow in size considerably over the next few years, and are looking
-
physical laws, or an implicit form of extra data examples collected from physical simulations or their ML surrogates. In medical domains, patient data is typically distributed across multiple hospitals
-
include but are not limited to: programming, algorithms, software development, communications and protocols, distributed systems, databases, mobile applications, operating systems, cloud computing, web
-
development, human-computer interaction, data analytics, user experience design, remote monitoring systems, energy optimization algorithms, and environmental impact modeling. Human-centric AI-driven sanitation
-
, the job involves developing algorithms for embedded systems that are designed to produce sensing and computation on the image plane, and on understanding the best ways to distribute visual computation along
-
computational tools to support the safe and ethical deployment of AI in clinical settings. The research focus is on AI performance monitoring, distribution shift detection, bias assessment, and stress testing
-
Computer Science, Southampton. The project is researching, developing and evaluating decentralised algorithms, meta-information data structures and indexing techniques to enable large-scale data search
-
project aims to address the current limitations of traditional frame-based sensors and associated processing pipelines with a new family of algorithmic architectures that mimic more closely the behaviours
-
. This project seeks to advance energy autonomy by optimising power conversion, storage, and distribution in such systems, enabling broader adoption in real-world applications. The project aims to develop a PMC