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

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 the key areas that will enable future revolutions in digital healthcare underpinned by Artificial Intelligence (AI) and Machine Learning, Data Science, Robotics and Imaging. TUM is ranked by QS in the top 25 in the world for natural sciences and engineering and is the only German university among the 10 most influential institutions in the field of Artificial Intelligence.

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 for this position, you will need to have a strong background in at least one of the following areas:

  • Computer vision;
  • Machine learning;
  • Medical image computing and image guided intervention.

Eligibility:  Students will be enrolled on the PhD programme of 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. Please check with us beforehand. If you have any questions regarding eligibility or the application process, please contact AI for Healthcare CDT Admissions 

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. Please also apply through the Imperial College admissions portal for the postgraduate research programme PhD in AI and Machine Learning

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.

PhD Studentship: AI-Driven Robotic Catheter System for Ultrasound Guided Endovascular Surgery

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 the key areas that will enable future revolutions in digital healthcare underpinned by Artificial Intelligence (AI) and Machine Learning, Data Science, Robotics and Imaging. TUM is ranked by QS in the top 25 in the world for natural sciences and engineering and is the only German university among the 10 most influential institutions in the field of Artificial Intelligence.

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: Minimally invasive surgery for vascular disease diagnostics and treatment requires a means to steer surgical tools through complex vessel trees. The procedure is usually performed manually, under  fluoroscopic guidance, which exposes the patient and staff to unnecessary radiation. This is a growing concern for the National Cancer Institute. The aim of this project is to explore non-fluoroscopy-based robotic catheter manipulation and tracking based on machine learning, bioelectrical localization and robotics. This project will explore an electrogenic sensorised catheter with AI-based localisation software, and a master-slave robotic catheter system capable of automatic targeting, based on a state-of-the-art robotic steering system for cooperative catheter insertion (EPSRC CathBot). Applicants should possess a keen interest in applied and translational science. Practical experience in robotics, non-holonomic control, haptics, hardware design and development, and algorithm development is highly desirable. A background in image processing would be welcome, while any exposure to medical technologies would be a plus. Good written and spoken English is essential.

Eligibility:  Students will be enrolled on the PhD programme of 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. Please check with us beforehand.

Application: To apply, please send a covering letter, full CV and contact details of two referees, one of whom must be academic, to Prof. Ferdinando Rodriguez y Baena. Please also apply through the Imperial College admissions portal for the postgraduate research programme PhD in AI and Machine Learning

Closing date: The deadline for applications is 28th August. Short-listed candidates will be informed by email and it is expected that interviews will take place the week commencing 10th September.

 


Supported by the Hamlyn Endowment Fund and research grants from our funding bodies and industrial partners, we are always interested in providing positions for talented researchers in imaging, sensing and robotics. The Centre aims to attract the brightest students from around the world, drawn by the unique opportunities offered within the Centre’s multidisciplinary environment and state-of-the-art facilities.

In addition to the PhD Studentships advertised for specific research projects, we also support applicants for the following fellowships to work within the centre:

Please contact Marianne Knight if you want to discuss specific details about any of the fellowships listed above.