Sort by
Refine Your Search
-
Listed
-
Employer
- University of Oxford
- ;
- Durham University
- AALTO UNIVERSITY
- DURHAM UNIVERSITY
- Heriot Watt University
- KINGS COLLEGE LONDON
- Imperial College London
- King's College London
- University of Cambridge
- City University London
- Heriot-Watt University;
- Swansea University
- UNIVERSITY OF VIENNA
- University of Cambridge;
- University of Liverpool
- University of London
- 7 more »
- « less
-
Field
-
analysed by bespoke machine-learning driven algorithms, combined with physical models, to de-noise images, identify features and correlate properties, giving critical insights into power loss pathways
-
About us: We are seeking experts in medical image deep learning to join our team and help develop novel computationally efficient segmentation algorithms. We welcome application from individual with
-
methods to improve the deployment, adaptation capabilities and safety of robots and critical infrastructures. The developed algorithms will be evaluated on legged robots, wheel-based robots and under
-
application. The successful candidate will work at the intersection of multi-disciplinary modelling, advanced AI algorithms, and decision-support tool development for various hydrogen technologies-based energy
-
system with integrated sensors. You should hold or be near completion of a PhD/DPhil with relevant experience in the field of robotics, biomedical engineering, information engineering, electrical
-
About Us We are seeking experts in medical image deep learning to join our team and help develop novel computationally efficient segmentation algorithms. We welcome application from individual with
-
quantum networks and quantum sensors. Point defects in wide-bandgap solids are an example, where the deterministic interaction between emitted photons and electronic and nuclear spins enables photon
-
Duration: 8 months or until 31 May 2026, whichever is sooner About the Role This is a research position for an EPSRC funded project entitled “Distributed Acoustic Sensor System for Modelling Active
-
accelerator laboratories, the R&D work of the Liverpool Hadronic Matter Group focuses on the development of Monolithic Active Pixel Sensors (MAPS), the state-of-the-art silicon sensor technology for high
-
(LiB’s). You will be responsible for: • Developing models and simulations of the electrode fabrication process, sensors, and actuators. • Developing a demonstrator of a soft sensing system that