[Jobs] PhD opportunity: AI for Autonomy in Surgical Interventions, University of Edinburgh
s.rama...@gmail.com
PhD studentship: AI for Autonomy in Surgical Interventions
We are recruiting for a fully funded PhD studentship in the area of AI-enabled robotics for surgical interventions. This project will be situated within the Centre for AI for Assistive Autonomy, a mission-driven research centre established using a UKRI Turing AI World Leading Researcher Fellowship awarded to Prof Subramanian Ramamoorthy, Professor of Robot Learning and Autonomy in the School of Informatics, University of Edinburgh. The appointee will also collaborate closely with Prof Mohan Sridharan and Dr Mohsen Khadem within the University of Edinburgh and with Professor Shervanthi Homer-Vanniasinkam, an internationally recognized clinician-scientist who is currently a Consultant Vascular Surgeon at Leeds Teaching Hospitals NHS Trust and Professor of Engineering & Surgery at University College London.
Through the centre, the appointee will also have the opportunity to interact with colleagues in a wide range of specialties across the University, including in machine learning and vision (e.g. Fisher, Mac Aodha, Bilen, Sevilla-Lara, Vergari), probabilistic programming (e.g. Narayanaswamy, Kammar, Belle), natural language understanding and interaction (e.g. Lascarides, Lapata, Gal), computational cognitive science and neuroscience (e.g. Lucas, Hennig, Nolan), as well as in robotics and neurotechnology (e.g. Vijayakumar, Nazarpour) and engineering of novel sensing and devices (Prodromakis, Koutsos, Amjadi). Beyond the university, the Centre will pursue collaborations with international teams including at The University of Texas at Austin (Stone), Stanford University (Kochenderfer), University of Bremen (Beetz) and Monash University (Burke).
The scientific focus of this project will be on developing new robot learning methods in the context of robotics for surgical interventions. This includes problems such as the following:
- Learning cross-modal generative models from data recorded during surgical procedures performed by human experts, with a view to enabling autonomous navigation and policy learning, including novel methods for learning from demonstration of long-horizon tasks.
- Learning of and with simulators, including potential connections with current methods for surgical simulators and their uses in planning and training.
- Developing methods for fine-grained skill quantification, mapping environmental and movement related features to higher level attributes determine surgical outcomes and recovery of the patient.
The ideal candidate for this position would have a UK 2:1 honours degree, or its international equivalent, in the area of robotics, artificial intelligence, computer science, engineering or related area with a strong background in quantitative methods and computer programming.
This studentship provides:
- Tuition fees for three years (Home or Overseas rate)
- Fourth year matriculation fee
- Stipend at UKRI level (£19,237 for 2024/25, subject to annual increment) for three and a half years
- Entitlement to paid leave (illness, maternity, etc.) in line with UKRI terms and conditions
Interested candidates should (1) send an email with their CV to caa-phd-r...@ed.ac.uk, and (2) follow the instructions in this web page to complete the formal application https://postgraduate.degrees.ed.ac.uk/?r=site/view&id=495, indicating in their cover letter their interest in the project and supervisor. Applications should be received by 10 April 2025, to be given full consideration for entry to the programme in October 2025.
Mazyar Taghavi
I hope this email finds you well.
I recently submitted my application to the program and afterward came across your research, which aligns closely with my academic interests. Unfortunately, I was unable to include your name as a proposed supervisor in my cover letter or the application portal at the time of submission.
I am very keen to pursue my PhD under your supervision, particularly given my recent research on AI for nanorobots in medicine. I would greatly appreciate the opportunity for you to review my application if possible. For your reference, my details are:
Name: Sayed Mazyar Taghavi
Student Number: S2734152
I have attached my CV for your convenience. Please let me know if there’s any additional information I can provide.
Thank you for your time and consideration. I look forward to your guidance.
Best regards,
Mazyar Taghavi
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