There are a number of potential PhD projects available for 2016/17 cohort that are linked to particular industrial partners. Choosing a PhD project that has an industry partner offers many benefits to both the student and the industry partner. As a student you will be provided with an additional industrial co-supervisor as a contact point. You will spend around 20% of your time at industrial R&D departments. This model for the CDT provides the PhD student with access to training, facilities and expertise not available in an academic setting. In addition, industrial partners provide student placements and industry workshops to demonstrate to students the potential application of their innovation and to highlight career pathways.
Apply for an industry project within the CDT
Here are the current PhD projects with an industry partner that are available to apply for:
103: Advanced cardiac magnetic resonance perfusion imaging
The aim of this project is to develop the next generation tools for advanced cardiovascular magnetic resonance (CMR) perfusion imaging. Novel CMR imaging sequences will be designed and implemented for both qualitative and quantitative perfusion imaging. This work will also involves the development of novel quantitative CMR reconstruction techniques. These new methods will be validated using our unique perfusion phantom and in patients.
113: Towards real-time optimization of parameter settings for Sonazoid™ enhanced ultrasound imaging
The project will investigate the acoustic properties of the microbubble contrast agent Sonazoid™ with the aim of developing real-time adaptive strategies for improved image quality. Techniques for improvement of both image contrast and image resolution will be explored. In addition, methods for determining quantitative flow parameters will also be studied.
319: “Comprehensive CRT CT Imaging (3CI)” This project will aim to exploit recent advances in dual energy CT scanners that provide high image contrast and with low radiation dose cardiac imaging at exceptional spatial and improved temporal resolution. The objective of this PhD will be the design, development and testing of an image processing and visualisation platform for extracting key indices of cardiac function and anatomy from cardiac CT imaging to predict the outcome of CRT and guide therapies.