Research Associate or Fellow in Real-Time AI for Surgical Robot Control at KINGS COLLEGE LONDON

job description
We are looking for a highly motivated person to join us and work on FAROS, a European research project dedicated to the advancement of functionally precise robotic surgery, https://h2020faros.eu, in collaboration with KU Leuven, Sorbonne University, Balgrist Hospital and SpineGuard.
Functional precision is defined as the degree to which the functional outcome of surgery conforms to the expected value for a successful, uncomplicated operation. FAROS aims to improve functional precision by integrating physical intelligence into surgical robotics.
Within the FAROS consortium, the research of the Department of Surgical and Interventional Engineering of the Faculty of Biomedical Engineering and Imaging is focused on the development of technologies for new image-guided interventions. Deep machine learning is being developed to interpret intraoperative data and link the assembled knowledge to autonomously perform surgical actions at operative rates well beyond human response capabilities.
The key activities concern the real-time processing of hyperspectral imagery and its integration into complex robotic systems. The recruited person will complement our multidisciplinary team and undertake research on machine learning, artificial intelligence and visual servoing of robot-controlled surgical instruments.
The position involves close and active collaboration with researchers, engineers and clinicians. Working with established platforms and relying on the software and mechatronic infrastructure already present within our teams is of paramount importance to ensure the cohesion of the project and strong links with the members of the consortium.
The successful candidate will design, develop and translate modular real-time software components for medical data processing, machine learning and visualization, and will also interface these with existing software and hardware components. More precisely, the candidate will develop algorithms that identify and follow the main anatomical landmarks, and will autonomously guide the robot to maximize the informative character of the captured data (active detection). The candidate will integrate his software developed into the consortium’s surgical robots.

This position will be offered on a 24-month fixed-term contract (last end date 12/31/2023)
This can be a full-time or part-time position – 50-100% full-time equivalent

Main responsibilities

  • Develop, validate and integrate real-time algorithms for computer-assisted intervention (CAI)
  • Contribute to project management tasks
  • Maintain precise and up-to-date technical and user documentation of the software delivered
  • Contribute to the dissemination of research through publications, open source software and public engagement activities

The above list of responsibilities may not be exhaustive, and the incumbent will be required to undertake the tasks and responsibilities reasonably expected in the context and classification of the position.

Skills, knowledge and experience
6TH YEAR
Essential criteria

1. Honors bachelor’s degree (2: 1 or higher) or equivalent in mathematics, engineering, physics, computer science or a related digital discipline
2. Doctorate or equivalent industrial experience in computer-assisted intervention or in a closely related field
3. Good knowledge of machine learning and computer vision algorithms
4. Solid knowledge and experience of using Python programming languages
5. Experience with scientific software packages such as PyTorch, Pandas, SciPy, NumPy, SciKit’s, OpenCV, ROS2, OROCOS, etc.
6. Experience in standard software engineering practices including version control systems and software testing methodologies
7. Experience working on system integration tasks
8. Ability to work with a variety of people

Desirable criteria

1. A demonstrable record of publications in peer-reviewed conference proceedings and scientific journals
2. Experience in project management
3. Understanding of image acquisition and relevant hardware components for real-time data acquisition and processing from existing and medical devices, including stereo cameras, force sensors and robot encoders. .

GRADE 7 – as above plus:
active participation in the planning of research projects;
the ability to coordinate the work of other staff;


Source link