job description
We are looking for a postdoctoral research associate to develop new artificial intelligence (AI) algorithms that take into account heterogeneous and asynchronous data sources captured before, during and after surgical procedures. Surgery’s transition from subjective experiences to evidence-based decisions is captured in the recently created field of “Surgical Data Science” (SDS). This translates into a growing demand for surgical and surgical workflows to become more data-driven. The multimodal nature of data available from edge computing capabilities will enable distributed online representation of surgical actions and progress towards the Internet of Medical Things (IoMedT).
In this role, the job holder will be responsible for designing and developing surgical data science algorithms that involve collecting, accessing and analyzing data from sensory surgical robotics. Specifically, the successful candidate will investigate multimodal data fusion strategies and leverage heterogeneous online data to create surgical processes that can be adapted to patient-specific surgical process models.
Candidates should have demonstrable experience in AI applied to multimodal data in the field of surgical data science or related fields, working with robotics-related applications and translating research into clinical practice. Applicants should have demonstrable experience with machine learning libraries, such as PyTorch and Multimodal Framework (MMF – Facebook AI Research). Knowledge of software engineering, version control software and experience working in a multi-developer team is desirable.
This project is part of a close collaboration with experts from the Department of Surgical and Interventional Engineering (SIE) around a trusted AI research pillar for sensory-rich surgical robotics.
The successful candidate must disseminate their research by presenting at scientific conferences, publishing in peer-reviewed journals, and providing open source software tools. Applicants should have a good track record of scientific publications in journals related to machine learning and/or computer-assisted intervention or equivalent conference publications. Applicants should have strong written and oral presentation skills.
The successful candidate will be based in the Department of Surgical and Interventional Engineering under the responsibility of Dr. Alejandro Granados, Senior Lecturer in Surgical Data Science, and working under the overall coordination of Dr. Christos Bergeles and Professor Tom Vercauteren. The successful candidate will have the ability to collaborate with other researchers, attend regular seminars, and apply their algorithms to other related clinical problems.
This position will be offered as a 2-year fixed-term contract (end date April 27, 2024)
This is a full-time position – 100% full-time equivalent
Main responsibilities
- Design and develop AI algorithms that take into account multiple heterogeneous and asynchronous data from sensor-rich surgical robotic systems.
- Support the development of surgical data science algorithms and device interoperability in the operating room
- Evaluate and validate the proposed methodology to accelerate its clinical translation
- Present the main results at scientific conferences
- Prepare high-quality manuscripts for publication
- Liaise with key collaborators in Biomedical Engineering and Surgery at King’s College London
The above list of responsibilities may not be exhaustive and the post holder will be required to undertake the duties and responsibilities reasonably expected within the scope and classification of the post.
Skills, knowledge and experience
Essential criteria
1. PhD in Machine Learning, Biomedical Engineering, Computer Vision, Surgical Robotics, or closely related field.
2. Good knowledge of computer engineering and device interoperability.
3. Demonstrable experience designing machine learning algorithms for multimodal, heterogeneous, and spatiotemporal data, including images, video, or audio.
4. Expertise in the use of machine learning related software packages, such as PyTorch, MMF or equivalent.
5. A track record of peer-reviewed publications in high quality scientific conferences and journals.
6. Excellent written and oral communication skills.
7. The ability to work with people from diverse backgrounds and specialties and to communicate technical concepts to people in other fields.
Desirable criteria
1. Experience in surgical data science and working with medical/surgical data.
2. Experience in proposing AI algorithms using sensor-rich data sources.
3. Demonstrable good to expert experience in software engineering, version control and continuous integration practices within multi-developer teams.
*Please note that this is a PhD level position, but candidates who have submitted their thesis and are awaiting their PhD will be considered. In these circumstances, the appointment will be in 5th year, spine 30 with the title of research assistant. Upon confirmation of the PhD award, the job title will change to Research Associate and the salary will increase to Grade 6.
More information
This post is subject to Disclosure and Barring Service clearance.
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