Mots-Clés

AI Computer Vision Surgery

Description

Projet Context

The MediCIS team of the LTSI is seeking a candidate for a 1-year funded post-doctoral position within the framework of the i-SaferS international research project, a collaboration between the University of Rennes and the Chinese University of Hong Kong.

The i-SaferS project focuses on the development of data- and model-based AI to automatically assess surgical contexts during robot-assisted hysterectomies, utilizing high-fidelity data provided by surgical robotic systems.

Role and Responsibilities

The successful candidate will lead research on automated surgical quality assessment across surgical phases. Key objectives include:

• Multimodal Analysis: Integrating video streams and kinematic data to evaluate surgical performance.
• Conceptual Development: Collaborating with international surgeons to refine and formalize the metrics of “surgical quality.”
• Algorithm Development: Designing, implementing, and comparing deep learning architectures for real-time quality estimation.
• Hybrid Modeling: Developing hybrid approaches that combine data-driven deep learning with a priori model-based knowledge.
• Uncertainty Quantification: Implementing Bayesian frameworks to account for uncertainty in AI predictions.

About the Environment

Located within the medical and midwifery university, the MediCIS/LTSI lab fosters a multidisciplinary environment where engineers and clinicians collaborate on high-impact societal projects. We are committed to responsible research, emphasizing social, environmental, and ethical considerations.

Candidate Profile

We are seeking a highly motivated researcher with:

• A PhD in Computer Science or a related field.
• Expert-level proficiency in Deep Learning and Computer Vision.
• Proven experience in multimodal data analysis.
• Preferred: A track record of publications in surgical video analysis or medical imaging.