For informal enquires please contact Jay Warnett (Associate Professor - Reader) j.m.warnett@warwick.ac.uk.
The CiMAT (Centre for Imaging, Metrology and Additive Technologies) team at University of Warwick seeks a creative and motivated research fellow in the area of deep learning for (X-ray) image processing.
The appointment is currently until 31 March 2027 (independent of start date), with a view to extend for an additional year dependent on successful project outcomes.
X-ray Computed Tomography (XCT) has been used in industry from the last few decades for materials development, assessment of manufacturing processes by identifying defects and porosity and creating next generation batteries.
It has been popularised given its ability to see inside of objects without sectioning, but its use is limited given the typically long acquisition times.
The overall aim of the project is to decrease image acquisition speed by acquiring less/noisier data, but still achieve a useful reconstructed image by employing a suite of AI/machine learning tools with limited impact on the task dependence.
Specifically, the successful candidate will develop models and methodologies to
- Upscale existing projection datasets by creating synthetic X-ray projections.
- Apply AI denoising techniques at acquisition of projections and post reconstruction.
Assess the impact against the task dependence of real datasets
We will consider applications for employment on a part-time or other flexible working basis, even where a position is advertised as full-time, unless there are operational or other objective reasons why it is not possible to do so.
