PhD Position in Computer Vision/Artificial Intelligence for Healthcare
Federated Learning for Scaling-up Surgical Activity Analysis
The operating room is a high-tech environment in which the surgical devices generate a lot of data about the underlying surgical activities. Our research group aims at making use of this large amount of multi-modal data coming from both cameras and surgical devices to develop an artificial intelligence system that can assist clinicians and staff in the surgical workflow. A core component of such an AI assistance system is the recognition of the surgical activities performed by clinicians and staff.
Existing recognition approaches are trained in a centralized manner: they require all the data to be stored on the same server. As institutions cannot easily share their data due to privacy concerns, current methods are often trained on limited datasets that are not representative of the surgical variability. Consequently, they do not generalize well to new clinical environments. A promising direction to address this issue is Federated Learning, in which a shared machine leaning model is trained by aggregating locally-computed updates.
This PhD position will focus on designing and evaluating novel methods based on deep learning and federated learning to recognize surgical activities from endoscopic videos. One major application will be the automated assessment of critical safety steps during the performance of the surgery. To carry out this work, the successful candidate will have access to a unique database of videos stemming from several clinical institutions and also have the possibility to interact with highly motivated clinical partners. By developing privacy-preserving computer vision and machine learning methods, he/she will facilitate the deployment of AI in hospitals.
Requirements:
- Master in Computer Science or equivalent
- C++/Python programming skills
- Strong knowledge in computer vision and machine learning
- Proficiency in English (oral and written)
- Experience with Deep Learning is a plus
Environment:
The position is located in Strasbourg, France. Strasbourg is a lively, green and cosmopolitan city situated in the heart of Europe and is also home to the European parliament. The successful candidate will be hosted within the AI team of the IHU institute at the University Hospital of Strasbourg. He/She will thereby have direct contact with clinicians, industrial partners and also have access to an exceptional international research environment offering state-of-the-art computing resources and unique clinical facilities. This PhD fellowship is funded by project AI4ORSafety, one of the 43 French national Chairs in Artificial Intelligence.
Benefits:
Cutting-edge research in an interdisciplinary and leading international research environment
Ability to work at the forefront of a rapidly growing field at the intersection of computer science, artificial intelligence and medicine
Development of real-world AI-based solutions for the operating room
To Apply:
Please send a long CV, motivation letter and academic transcripts to Nicolas Padoy.
Links:
ICube laboratory
IRCAD Institute
IHU MixSurg Institute
Laboratory of excellence CAMI