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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”.

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. Research in these relevant areas, at Imperial, is concentrated in the Faculties of Engineering, Medicine and Natural Science, as well as the Data Science Institute and Institute of Global Health Innovation. At Imperial, there are 40+ academics already working in AI, Robotics and Imaging related research and over 100 academics researching the applications of these technologies in Healthcare. 

Scholarship: This is a full-time PhD research studentship, including full stipend and tuition fee costs for a Home student, available for 4 years starting 1st October 2020. The studentship will be available for up to four years, with a stipend equivalent to UKRI rates (approx. £17,285 tax free for 2020/21 and subject to change for future years). This also covers travel support for fieldwork, conferences and industrial visits. The student will be based at Imperial College London and is expected to spend at least one year in TUM (two 6-months periods).

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 working within the AI4Health CDT at Imperial College London, so they must meet and follow the application requirements for the CDT. If you have any questions regarding eligibility or the application process, please contact AI for Healthcare CDT Admissions ai4health-admissions@imperial.ac.uk

Application: To apply, please send a covering letter, full CV and contact details of two referees, one of whom must be academic, to Dr. Stamatia Giannarou (stamatia.giannarou@imperial.ac.uk).

Closing date: The deadline for applications is 4th September. Short-listed candidates will be informed by email and it is expected that interviews will take place the week commencing 10th 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”.

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. Research in these relevant areas, at Imperial, is concentrated in the Faculties of Engineering, Medicine and Natural Science, as well as the Data Science Institute and Institute of Global Health Innovation. At Imperial, there are 40+ academics already working in AI, Robotics and Imaging related research and over 100 academics researching the applications of these technologies in Healthcare.

Scholarship: This is a full-time PhD research studentship, including full stipend and tuition fee costs for a Home student, available for 4 years starting 1st October 2020. The studentship will be available for up to four years, with a stipend equivalent to UKRI rates (approx. £17,285 tax free for 2020/21 and subject to change for future years). This also covers travel support for fieldwork, conferences and industrial visits. The student will be based at Imperial College London and is expected to spend at least one year in TUM (two 6-months periods).

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 working within the AI4Health CDT at Imperial College London, so they must meet and follow the application requirements for the CDT. If you have any questions regarding eligibility or the application process, please contact AI for Healthcare CDT Admissions ai4health-admissions@imperial.ac.uk

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.

Closing date: The deadline for applications is 4th September. 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 Miss Marina Hall (marina.hall@imperial.ac.uk) if you want to discuss specific details about any of the fellowships listed above.