Brief description and estimated completion date of the project :  

Knee injuries are the most frequent traumatic pathologies in sports. Among other things, the management of cruciate ligament (CL) pathologies necessarily raises the question of return to sport, whether competitive or non-competitive, and even constitutes a public health issue. This project therefore aims to improve knee injury prevention by developing an artificial intelligence algorithm for classifying healthy and experimentally impaired motor performance. We hypothesize that training a neural network model to discriminate between time series of biomechanical signals of healthy and impaired motor performance will enable better prediction of knee injury risk. This project therefore aims to produce a proof of concept of the ability of artificial intelligence to identify subtle differences in force production as objective markers of functional impairment, whether for predictive purposes and/or post-surgical follow-up. Project completion: June 2026 (18-month contract).

Missions / functions performed : 

The post-doctoral researcher will mainly be involved in experimental research (data collection) and computational research (development of processing algorithms). He or she will mobilize mathematical and computational methods to optimize programming and propose appropriate tools.

Main activities (in order of importance) : 

Gathering experimental data involving the human body on motor tasks involving the lower limbs (setting up experimental design, recruitment, test taking); Providing researchers in a given field with expertise in the use of mathematical methods and computing techniques; Guiding the choice of relevant methods and tools according to the problem posed; Designing methods for modeling, calculating and visualizing results; Reviewing the literature (deep learning for health data exploitation) and the state of the art in data processing techniques (image transformation, data fusion); Statistical analysis; Communicating knowledge through presentations and research reports (original scientific articles); Supervising student trainees (Master's degree).

Event - Objective result(s) fixing the end of the agent's mission :

Completion of the database (n = 100 participants) and operational classification of motor performance (confusion matrix, interpretability) Drafting of a research report in the form of an original scientific article for submission to a peer-reviewed journal.

Assessment and monitoring of results achieved :  

Construction of a provisional schedule listing the progress of the various stages/missions of the project (experimental and computational aspects). Monthly meetings with the project leaders, with a presentation of recent progress at each stage.

Finance: (DEEPKNEE) - Project supported by IDEX UGA - Grenoble Alpes 2024 Research Initiatives.

Document to be sent :

Please send your CV and a letter explaining your motivation to work on this subject and the skills you possess. The document can be written in English or in French.

Put the title of the email subject: [Post-Doc]: Application - Name

Contacts:

• Dawood AL CHANTI, Associate Professor, dawood.al-chanti@grenoble-inp.fr

• Julien FRERE, Associate Professor, julien.frere@gipsa-lab.grenoble-inp.fr