PhD student in medical image processing (M/F)

CNRS; France; Sur place; EUR 18 000 - 22 000; Plein temps

Résumé du poste

Le TIMC laboratoire du CNRS recherche un/une doctorant(e) dans le cadre du projet ADAGIO pour développer des méthodes de segmentation basées sur l’IA afin d’aider le guidage des robots endoscopiques. Le candidat travaillera au sein d’une équipe interdisciplinaire et collaborera avec Grenoble University Hospital et d’autres partenaires du consortium.

Le titulaire d’un M2 ou d’un diplôme d’ingénieur en informatique ou IA, avec une expérience en traitement d’images médicales idéalement, publiera

Qualifications

• Titulaire d’un M2 ou d’un diplôme d’ingénieur en informatique ou IA.
• Idéalement expérience en traitement d’images médicales.
• Bonne connaissance des outils IA et en anglais scientifique.

Responsabilités

• Développer des méthodes de segmentation IA pour les images echo-endoscopiques.
• Publier les résultats avec l’appui des encadrants.
• Participer aux événements doctorants TIMC et déplacements possibles à Strasbourg.

Connaissances

IA segmentation

PyTorch

TensorFlow

Technical writing

Literature review

Zotero

Formation

M2 ou diplôme d’ingénieur en informatique ou IA

Outils

PyTorch

TensorFlow

Zotero

Description du poste

Organisation/Company CNRS Department recherche Translationnelle et Innovation en Médecine et Complexité Research Field Engineering Computer science Mathematics Researcher Profile First Stage Researcher (R1) Application Deadline 24 Sep 2026 - 23:59 (UTC) Country France Type of Contract Temporary Job Status Full-time Hours Per Week 35 Offer Starting Date 1 Nov 2026 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No

Offer Description

You will be working within the TIMC laboratory (Translational Research and Innovation in Medicine and Complexity), a joint research unit (CNRS, UGA, G-INP, VetAgro Sup) comprising nearly 300 members, including 70 PhD students, divided into 10 teams. TIMC undertakes innovative projects and places translational research at the heart of its activities, drawing on close collaboration with Grenoble University Hospital. The laboratory is a key player in innovation thanks to the close link between its research and the needs of society. Furthermore, our research is commercialised through the creation of start-ups, which demonstrates its economic potential.
The laboratory offers a stimulating interdisciplinary environment, where clinicians and researchers work together on the application of computer science and applied mathematics in the fields of biology and health. You will work in a rewarding professional environment characterised by a positive atmosphere and a collaborative spirit. You will benefit from personalised support throughout your career. Committed to equality and diversity, TIMC values the richness of different backgrounds and welcomes anyone wishing to contribute to its research projects. Located within the health campus of Grenoble University Hospital, the laboratory offers you a stimulating scientific working environment and a pleasant living environment, surrounded by mountains!

The ADAGIO project focuses on assisting with endoscopic gallbladder drainage in cases of acute cholecystitis using continuous, tendon-driven robots. The PhD student's role will be to develop AI-based image segmentation methods for echo-endoscopy images to guide the robots: the PhD student will carry out their research project with the support of their supervisors. They will be required to keep up to date with the state of the art in the field, develop innovative AI-based segmentation models, collaborate with the relevant members of the consortium, publish their research with the assistance of their supervisors, and actively participate in the team's collective activities. They will also be expected to take part in events organised for PhD students at the TIMC and its doctoral school. The PhD student may be required to travel to Strasbourg to attend or assist with the animal data acquisition campaign.

Ideal candidate

A student holding an M2 or an engineering degree in computer science or AI, ideally with internship experience in medical image processing.

Technical skills

• developing AI segmentation models
• familiarity with PyTorch and TensorFlow
• drafting technical documents and reports
• conducting literature reviews and maintaining a reference library using tools such as Zotero

Personal qualities

• taking the initiative and working independently
• ability to work as part of a team with colleagues from diverse backgrounds
• team spirit

To develop AI-based image segmentation methods for echo-endoscopy images to guide robots.