University of Leeds Featured PhD Programmes
European Molecular Biology Laboratory (Heidelberg) Featured PhD Programmes

PhD Studentship: Confidence-driven Robotic Ultrasound Tissue Scanning for Surgical Resection Guidance


Joint Academy of Doctoral Studies

This project is no longer listed on FindAPhD.com and may not be available.

Click here to search FindAPhD.com for PhD studentship opportunities
Dr S Giannarou No more applications being accepted Funded PhD Project (UK Students Only)

About the Project

Imperial College London and the Technical University of Munich (TUM) have launched a Joint Academy of Doctoral Studies (JADS) with the aim of fostering closer collaboration between London and Munich research, innovation and education communities.

The Joint Academy of Doctoral Studies is a bilateral, cross-disciplinary programme aimed at fostering research collaborations at the doctoral level and beyond, in fields that are highly relevant to both Imperial College London and TUM. This round of the programme focuses on the theme of “Artificial Intelligence, Healthcare and Robotics” and is supported by the UKRI Centre for Doctoral Training in AI for Healthcare. Imperial and TUM have international excellence in key areas to enable future revolutions in digital healthcare underpinned by Artificial Intelligence (AI) and Machine Learning, Data Science, Robotics and Imaging.

Scholarship:

This is a full-time PhD research studentship, including full stipend and tuition fee costs, for at least 3 years, starting 5th October 2020. The studentship pays a stipend equivalent to UKRI rates (approx. £17,285 paid monthly tax-free for 2020/21 and is subject to inflation change in future years), covers full tuition fees for a Home/UK student and travel support for conferences and visits to TUM. Students are also asked to be prepared to work at TUM in Germany (Such placement could be up to 6-12 months, depending on the project plan and progress). This may need to be reviewed, however, depending on how the guidance on public health might change in either country in response to developments of the Covid-19 pandemic.

Research Theme:

Intraoperative Ultrasound (iUS) has been established as an efficient tool for tissue characterisation during brain tumour resection in neurosurgery. It allows precise visualization of vital structures, progression of tumour resection, and management of immediate complications. However, tissue scanning requires significant training to obtain high-quality images, and the interpretation of US data remains challenging. To address these challenges, the aim of this project is to build a cognitive robotic platform for iUS tissue scanning to optimise the confidence in intraoperative tissue characterisation and improve both the efficacy and safety of tumour resections. A key application of the proposed platform is the scanning of brain tissue to guide tumour resection but its versatile nature makes it suitable for the scanning of any organ. To apply, you will need to have a strong background in at least one of these areas:
• Computer vision;
• Machine learning;
• Medical image computing and image guided intervention.

Eligibility:

Students will be enrolled in the UKRI Centre for Doctoral Training in AI for Healthcare (AI4Health) at Imperial College. The scheme is open to Home/UK students. Applicants who have a non-British European passport, are either settled in the UK or have been ordinarily resident in the UK throughout the five-year period prior start of studies, may be eligible as well. If you have any questions please contact AI for Healthcare CDT Admissions ([Email Address Removed]).

Application:

To apply, please send a covering letter, full CV and contact details of two referees, one of whom must be an academic, to Dr. Stamatia Giannarou ([Email Address Removed]). Please also apply through the admissions portal for the postgraduate research programme PhD in AI and Machine Learning (https://www.imperial.ac.uk/study/pg/apply/how-to-apply/apply-for-a-research-programme-/).

Closing date:

The deadline for applications is 28th August. Short-listed candidates will be informed by email. Interviews are likely to start the week commencing 10 September.
Search Suggestions

Search Suggestions

Based on your current searches we recommend the following search filters.



FindAPhD. Copyright 2005-2020
All rights reserved.