Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
- ;
- University of Sheffield
- University of Glasgow
- Heriot Watt University
- ; The University of Edinburgh
- Cardiff University
- ; Swansea University
- Cranfield University
- Durham University
- UNIVERSITY OF SOUTHAMPTON
- University of Oxford
- ; City St George’s, University of London
- ; University of Warwick
- Imperial College London
- Lancaster University
- Queen's University Belfast
- University of Birmingham
- University of Leeds
- University of Nottingham
- VIETNAMESE-GERMAN UNIVERSITY
- ; Cranfield University
- ; The University of Manchester
- ; University of Birmingham
- ; University of Bradford
- ; University of Nottingham
- ; University of Reading
- ; University of Sheffield
- Abertay University
- Birmingham City University
- DURHAM UNIVERSITY
- Manchester Metropolitan University
- Nature Careers
- Nottingham Trent University
- QUEENS UNIVERSITY BELFAST
- The University of Southampton
- UNIVERSITY OF EAST LONDON
- UNIVERSITY OF VIENNA
- University of Bristol
- University of Cambridge
- University of East London
- University of Manchester
- University of Newcastle
- University of Surrey
- University of the West of England
- 34 more »
- « less
-
Field
-
Introduction The post is at the Department of Computer Science and is associated with the Integrated Quantum Networks (IQN) Research Hub. This newly funded hub is at the forefront of advances toward
-
We are seeking a Research Fellow to perform research on deployment of machine-learned models for health analytics on distributed IoT/edge/cloud systems using transprecise computing and contribute
-
Deadline: 31 August 2025 A fully funded 3.5 year PhD position is available to work on the project titled “Scalable benchmarking for digital quantum computers based on blind testing”. This position
-
, including scenario-based and tube-based approaches, to ensure reliable operation despite significant uncertainty in weather, demand and energy prices. In collaboration with UK Power Networks and SSE Energy
-
Federated learning (FL) is a privacy-preserving distributed learning paradigm that allows different clients to create a shared AI models without having to share their data. Despite these advantages
-
in distributed database systems, information retrieval, computer networking or semantic web. The post does not involve working outside of the UK for over 30 days in a row or over 90 days in a year. For
-
, University of London in August 2024. As a PhD candidate, you'll become an integral part of the School of Science and Technology (proud member of the Alan Turing University Network) and be supervised by leading
-
opportunities, including hybrid working for some roles. Generous pension scheme. A wide range of discounts and rewards on shopping, eating out and travel. A variety of staff networks, providing opportunities
-
mediated entanglement for distributed quantum networks. Optical readout of electronic and nuclear spins on the single spin level can give rise to nanoscale sensors of magnetic field, temperature and pressure
-
Funding for: UK/Home Students We invite applications for a fully funded PhD research scholarship in “Unsupervised Machine Learning for Cardiovascular Image Analysis”. This opportunity is available