Sort by
Refine Your Search
-
continuous water quality measurement in rivers. This is in response to the national need to monitor wastewater overflow spills. The technology has the potential to be deployed to 1000’s of UK river locations
-
test a variable stiffness catheter. Conduct in-vivo animal trials of the prototype. Do market discovery of the technology by actively participating in the Commercialization Journey programme offered by
-
labeling and chemical shift imaging with support of existing team members. You will set up real-time image processing to high quality data collection. The opportunity for bold, discovery science is how
-
. To fill in this gap, in collaboration with industrial partners, the research will develop novel Machine Learning and Computer Vision methods for detecting and localising. These will be used to develop
-
(see below). There is currently one fellowship available where the successful candidate will join one of our Cardiovascular Research Teams, details as follows: - BRC Theme: Cardiovascular / Imaging
-
to develop and validate paediatric bone models through a combined computational and experimental approach, in collaboration with clinical partners at the Sheffield Children’s Hospital. The ideal candidate will
-
application in a working environment in some of the following: Insect neuroscience/behaviour; Electrophysiology; Data/image/video analysis; Drosophila genetics; Electron microscopy; Computer programming
-
informatics, and energy systems, and offers the opportunity to directly contribute to the operation and design of next generation fusion facilities. This EngD project is set within the Fusion Engineering CDT
-
, computer vision, medical/image analysis is essential. Experience of research (or interest in) in one or more of the following: deep learning; big data management; computational pathology; medical imaging
-
-resolution imaging and reconstruction of neural tissues (see https://ist.ac.at/en/research/siegert-group/). Leveraging computational tools such as machine learning and topological data analysis, we will