Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- KINGS COLLEGE LONDON
- ;
- Durham University
- University of Oxford
- King's College London
- Manchester Metropolitan University
- AALTO UNIVERSITY
- DURHAM UNIVERSITY
- UNIVERSITY OF VIENNA
- University of Cambridge
- University of London
- University of Nottingham
- University of Liverpool
- University of Birmingham
- Heriot Watt University
- University of Glasgow
- Imperial College London
- MOHAMMED VI POLYTECHNIC UNIVERSITY
- Nature Careers
- University of Bath
- University of Manchester
- University of Nottingham;
- ; University of Cambridge
- Aston University
- Cardiff University
- European Magnetism Association EMA
- John Innes Centre
- Kingston University
- Medical Research Council
- Oxford Brookes University
- Swansea University
- University of Essex;
- University of Lincoln
- University of Newcastle
- University of Oxford;
- 25 more »
- « less
-
Field
-
assays, to play a key role in development and deployment of cutting-edge methods to detect cancer earlier than traditional methods About You Experience of translational research using human samples
-
-Watt have a long–standing track record in researching ground-breaking single photon detection and applications in quantum communications and single-photon imaging. With single-photon avalanche diode
-
of using Bayesian methods in both model development and fitting. Previous experience and knowledge of research methods and study design in clinical trials. Knowledge of Good Clinical Practice (GCP) in
-
methodology, theory, and applications across the areas of Bayesian experimental design, active learning, probabilistic deep learning, and related topics. The £1.23M project is funded by the UKRI Horizon
-
, imaging and timing applications. In this project, we will: Develop Bayesian deep learning methods for event-based data, including single-photon detections and neuromorphic camera data. Investigate Bayesian
-
, or single-photon detectors (used for single-photon Lidar), that natively produce event-like data that is compatible with spiking networks. Similarly, detection events from RF (radar and electronic
-
detection framework for tipping points. Contribute to the design of scalable and interpretable forecasting strategies for large climate simulators, integrating adaptive sampling and Bayesian techniques
-
related to gravitational wave astronomy. The primary aim will be the development of advanced approaches for computational Bayesian Inference to measure the properties of Compact Binary Coalescence signals
-
methods for multimodal imaging and real-time analysis in colorectal cancer screening and treatment. They will contribute to the design of AI algorithms for polyp detection, tissue characterization, and
-
) Experience of working with multiple stakeholders in complex systems. Experience in large scale simulations Experience in Bayesian methods Experience using CRAFTY agent based model Full details of the role and