Sort by
Refine Your Search
-
Listed
-
Employer
- ;
- University of Nottingham
- ; Swansea University
- ; City, University of London
- ; Newcastle University
- ; University of Plymouth
- Swansea University
- ; Brunel University London
- ; Manchester Metropolitan University
- ; UCL
- ; University of Exeter
- ; University of Leeds
- ; University of Southampton
- ; Xi'an Jiaotong - Liverpool University
- Brunel University
- 5 more »
- « less
-
Field
-
by Manchester United FC. This approach to real-time imaging will be integrated into an AI imaging analytics package to promote automatic injury detection and aid player diagnosis by the partner medical
-
Alpes. Thanks to increasingly precise and sophisticated medical imaging techniques and fast-growing powerful image morphing tools, there are ways to predict the appearance of a patient's face after
-
-to-roll technology and post-processing to harvest nanoparticles on a scale beginning with grams, heading for kilograms and with the potential for tonnes – representing a revolutionary paradigm-shift in (bio
-
“interrupted” tests whereby the process is paused or slowed to allow information to be collected at a series of discrete time or load steps. This results in an estimated interpolation of events between capture
-
Duration of study: Full time - 4 years fixed term (1y MRes + 3y PhD) Starting date: September 2024 Primary Supervisor: Prof. Ilias Tachtsidis, Department of Medical Physics and Biomedical
-
experience in the areas of computer science, image processing, high performance computing, mathematics, and medicine. Dr Yanda Meng (Computer Vision, Medical Image Analysis, LLM), Prof Aline Villavicencio
-
Supervisory Team: Joseph Lifton, Thomas Blumensath, Mark Mavrogordato Project description: Working closely with Rolls Royce, this PhD will establish advanced, but practical 3D X-ray imaging methods
-
to pathogens including SARS-CoV-2. This PhD will help determine if MS and AD ChP pathology leads to altered TH transport that then causes chronic inflammation and neurodegeneration in MS and AD. The student will
-
Modern deep learning techniques achieve human-like performance in many medical image analysis tasks, including the identification of anomalous tissue/pathology from medical scans. To be trained
-
AI has the potential to revolutionise healthcare, providing tools for fast and reliable analysis and interpretation of medical data. For instance, many deep learning models for medical image