Research Engineer F/M on Longitudinal Image-based Measurement of Scoliosis Change

Research Engineer F/M on Longitudinal Image-based Measurement of Scoliosis Change

The Inria Grenoble research center groups together almost 600 people in 26 research teams and 8 research support departments.

Staff is present on three campuses in Grenoble, in close collaboration with other research and higher education institutions (University Grenoble Alpes, CNRS, CEA, INRAE, …), but also with key economic players in the area.

Inria Grenoble is active in the fields of high-performance computing, verification and embedded systems, modeling of the environment at multiple levels, and data science and artificial intelligence. The center is a top-level scientific institute with an extensive network of international collaborations in Europe and the rest of the world.

Position: Research engineer at INRIA – Grenoble, KINETIX team

Date: The position is open for a start in Oct 2026.

Advisors: The retained candidate will be advised by Sergi Pujades, Jéan-Sébastien Franco and Edmond Boyer at Kinetix INRIA.

Context

Adolescent Idiopathic Scoliosis (AIS) is a three-dimensional spinal deformity affecting 1–4% of the population, which can limit spinal mobility and often progresses from mild or moderate to severe during puberty. Treatments typically include bracing or surgery in severe cases, and scoliosis is usually measured using the Cobb angle. However, this single-angle measurement oversimplifies the complex 4D deformity, making it difficult to track the evolution of the condition or the impact of treatments on mobility over time. To address this, the LIMSC project aims to develop AI-based tools to analyze longitudinal 3D morphological and kinematic changes in AIS patients. LIMSC will collect image-based body surface shape, motion, and biplanar radiographies over time in a clinical setting, obtain highly accurate 3D reconstructions of the patients, and register the patients’ data in a common spatial and temporal frame to identify patterns and generate novel AIS classifications. LIMSC key insights include markerless body motion capture, accurate 3D reconstructions, and modeling changes with an Adolescent Growth Digital Twin. By combining these methods, LIMSC seeks to provide a comprehensive understanding of how treatments affect patient function, posture, and overall well-being, going beyond the limited view offered by static radiographs.

Objectives

LIMSC will leverage retrospective datasets of multi-view images of patients collected prior to the project.

These videos will be processed with the current best 3D reconstruction algorithm (1), and SKEL (2) will be registered to the reconstructions to obtain 4D temporal trajectories.

The processing will take place on the GRICAD cluster ( ). Creating a dedicated processing pipeline will be key in the project, so that novel acquired data can be automatically processed, and a quality control can be effectuated.

As SKEL (2) was learned from an adult cohort and not adolescents, improvements will need to be added to the model and the registration pipeline. Also, as the back of AIS patients might exhibit gibossities and SKEL does not model them, further improvements will be required.

(1) Toussaint, Briac, Diego Thomas, and Jean-Sébastien Franco. "ProbeSDF: Light Field Probes For Neural Surface Reconstruction." In Proceedings of the Computer Vision and PatternRecognition Conference, pp. . 2025.

(2) Keller, Marilyn, Keenon Werling, Soyong Shin, Scott Delp, Sergi Pujades, C. Karen Liu, and Michael J. Black. "From Skin to Skeleton: Towards Biomechanically Accurate 3D Digital Humans." ACM Transactions on Graphics (TOG) 42, no. 6 (2023): 1-12.

Candidate Profile

• A master in Computer Science or Applied Mathematics (mandatory).
• Strong mathematical background – geometry – optimization techniques.
• Good Oral and written English.
• Preliminary experience in the following areas is a plus: computer vision – 3D point clouds – registration techniques – geometry processing – 3D pose estimation.

A specific section in the application letter must explain the personal experience in these areas.