Phd Position F/m Real-time Surgical Assistant for

Le descriptif de l’offre ci-dessous est en Anglais_ **Niveau de diplôme exigé **:Bac + 5 ou équivalent **Fonction **:Doctorant **A propos du centre ou de la direction fonctionnelle**: The Inria center at Université Côte d'Azur includes 42 research teams and 9 support services. The center’s staff (about 500 people) is made up of scientists of different nationalities, engineers, technicians and administrative staff. The teams are mainly located on the university campuses of Sophia Antipolis and Nice as well as Montpellier, in close collaboration with research and higher education laboratories and establishments (Université Côte d'Azur, CNRS, INRAE, INSERM...), but also with the regional economic players. With a presence in the fields of computational neuroscience and biology, data science and modeling, software engineering and certification, as well as collaborative robotics, the Inria Centre at Université Côte d'Azur is a major player in terms of scientific excellence through its results and collaborations at both European and international levels. **Contexte et atouts du poste**: Our project is to develop a real-time surgical assistant that leverages AI and augmented reality to provide precise dissection guidance, enhancing surgical accuracy. **Team** The PhD thesis will be conducted within 2 research teams: Epione and Stars The STARS research team combines advanced theory with cutting-edge practice focusing on cognitive vision systems. Scientific context **Mission confiée**: **Detailed description**: Surgery has evolved from open surgery to mínimally invasive and robot-assisted surgery. Today, cutting-edge technologies such as connected operating rooms, digital twins, AI, and augmented reality (AR) are revolutionizing surgical care. These innovations promise more precise surgery with anticipated post-operative results. Thanks to the massive acquisition of video data from operations, it is becoming possible to analyze interventions in distinct phases and gestures, carrying the potential to offer real-time interpretation and contextual feedback to the surgeon. In parallel, advanced computer vision methods have shown impressive performance in object detection, segmentation, tracking, and action recognition, thanks to machine learning on vast databases. However, these models do not generalize well to surgical videos. More recently, foundation models have enjoyed great success in a variety of tasks, but the difference in distribution between Internet videos and surgical videos remains a challenge. This project aims to adapt Transformer-based methods and foundation models for surgical videos. We aim to develop a surgical assistant providing real-time dissection advice via AR. Using AI to recognize anatomical structures, instruments, and phases of the procedure, our system will project a precise dissection plan onto the surgical field, functioning as a "GPS for surgeons". In particular, the system will: - Track surgical instruments to ensure precise tissue interactions. - Recognize and classify anatomical structures to guide dissection. - Analyze surgical phases and provide contextual feedback. - Project AR guidance for intuitive visual cues. **Principales activités**: We are seeking an engineer with a strong background in computer vision, deep learning, and machine learning. **Main activities**: - Analyze the requirements of doctors and study the limitations of existing solutions. - Propose a new algorithm for a surgical assistant - Evaluate and optimize the proposed algorithm on the targeted video datasets - Oral presentation and Write reports - Submit scientific papers to conferences **Compétences**: With theoretical knowledge in Computer Vision, OpenCV, Mathematics, Deep Learning (PyTorch, TensorFlow), and technical background in C++ and Python programming, and Linux. **Avantages**: - Subsidized meals - Partial reimbursement of public transport costs - Leave: 7 weeks of annual leave + 10 extra days off due to RTT (statutory reduction in working hours) + possibility of exceptional leave (sick children, moving home, etc.) - Possibility of teleworking and flexible organization of working hours - Professional equipment available (videoconferencing, loan of computer equipment, etc.) - Social, cultural and sports events and activities - Access to vocational training **Rémunération**: Gross Salary per month: 2100€ brut per month (year 1 & 2) and 2190€ brut per month (year 3) **Informations générales**: - **Thème/Domaine**: Neurosciences et médecine numériques Statistiques (Big data) (BAP E) - **Ville**: Sophia Antipolis - **Centre Inria**: Centre Inria d'Université Côte d'Azur - **Date de prise de fonction souhaitée**: 2024-11-01 - **Durée de contrat**: 3 ans - **Date limite pour postuler**: 2024-10-31 **Consignes pour postuler**: **Sécurité défense**: Ce poste est susceptible d’être affecté dans une zone à régime restrictif (ZRR), telle que définie d