Research Associate / Research Fellow in Trustworthy Artificial Intelligence for Surgical Imaging

London (Greater)
Grade 6: £41,386-£48,414 or Grade 7: £49,737-£55,306 per annum, including London Weighting Allowance
18 May 2023
End of advertisement period
15 Jun 2023
Academic Discipline
Clinical, Pre-clinical & Health
Job Type
Research Related
Contract Type
Fixed Term
Full Time

Job description

We are seeking a Post-doctoral Research Associate to develop novel trustworthy artificial intelligence (AI) algorithms able to extract actionable information from surgical imaging data. 

Candidates should have demonstrable experience in AI applied to imaging data in the field of surgical data science or related fields, in working with robotic-related application, and in translating research into surgical workflows. Candidates are expected to have demonstrable experience with machine learning libraries, such as PyTorch, and robotics frameworks such as ROS. Familiarity with software engineering, version control software, and experience working within a multi-developer team is desirable. 

The post involves close and active collaboration with researchers, engineers and clinicians. The post-holder will take part in the FAROS European Project (, the Wellcome NeuroPPEye project ( and contribute to the Wellcome / EPSRC Centre for Medical Engineering - Trustworthy AI for Sensory-rich Surgical Robotics research pillar ( Working with established platforms and building on the software and mechatronics infrastructure already present within our teams if of paramount importance to ensure project cohesion and strong links with the members of the consortium. 

The successful candidate is expected to disseminate their research through presenting at scientific conferences, publishing in peer-reviewed journals, and providing open-source software tools. Candidates are expected to have a strong track record (for their career stage) of scientific publications in machine learning and/or computer-assisted intervention-related journals or equivalent conference publications. Candidates should have strong written and oral presentation skills. 

The successful candidate will be based in the Department of Surgical and Interventional Engineering reporting to Prof Tom Vercauteren. The successful candidate will have the ability to collaborate with other researchers, supervise junior researchers (for Research Fellows), attend regular seminars, and apply their algorithms to other related clinical problems. 

This post will be offered on an a fixed-term contract for up to 21 months until 31 March 2025. 

This is a full-time post - 100% full time equivalent

Key responsibilities

•         Develop, validate and integrate trustworthy algorithms for computer-assisted intervention (CAI)  

•         Contribute to project management  

•         For Research Fellows: Contribute to junior research member supervision 

•         Maintain accurate and up-to date technical and user documentation of the delivered software 

•         Contribute to the dissemination of the research through publications, open-source software and public engagement activities 

The above list of responsibilities may not be exhaustive, and the post holder will be required to undertake such tasks and responsibilities as may reasonably be expected within the scope and grading of the post.  

Skills, knowledge, and experience 

Essential criteria  

1.       PhD or equivalent industrial experience in Computer Assisted Intervention or a closely related field 

2.       Good knowledge of machine learning and computer vision algorithms 

3.       Solid knowledge of and experience using the Python programming language 

4.       Experience with scientific software packages such as PyTorch, Pandas, SciPy, NumPy, SciKit’s, OpenCV, ROS2, etc. 

5.       A demonstrable record of publications in top-ranked peer-reviewed conference proceedings and scientific journals in the field 

6.       Ability to work with a variety of people 

7.       For Research Fellows (G7): Experience in planning research projects and coordinating the work of other staff 

Desirable criteria

1.       Understanding of image acquisition and hardware components relevant to real-time data acquisition and processing from existing and medical devices including stereo cameras, force sensors, and robot encoders. 

2.       Solid knowledge of and experience using the C++ programming language 

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