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Post-doctoral Research Visit F/m Advanced Modeling and Ai for Personalized Myopia Treatment
il y a 2 semaines
Le descriptif de l’offre ci-dessous est en Anglais_
**Type de contrat**: CDD
**Niveau de diplôme exigé**: Thèse ou équivalent
**Fonction**: Post-Doctorant
**Contexte et atouts du poste**:
**Context**
The MIMESIS team at INRIA is a leading research group at the crossroads of scientific computing, machine learning, medical imaging, and control. Our mission is to develop cutting-edge digital tools for personalized medicine, particularly through the creation of **digital twins** and advanced **numerical methods** to assist medical interventions. With a strong foundation in **biomechanical modeling of soft tissues** and real-time computational methods, we work closely with clinicians to translate scientific innovations into practical healthcare solutions — from surgical planning to augmented reality and robotic control.
As part of this commitment, the MIMESIS team is now involved in **PREMYOM**, a large-scale, five-year biomedical innovation project focused on **personalized myopia treatment for children**. Coordinated by **EssilorLuxottica** and funded by the **France 2030** national plan, the PREMYOM consortium brings together six prestigious French partners from research, industry, and healthcare**:INRIA**, **Hôpital Fondation Adolphe de Rothschild**, **Institut de la Vision**, **Institut Mines-Télécom**, and **InSimo**.
PREMYOM aims to establish a new standard in pediatric eye care by developing predictive models and digital tools that account for the anatomical, optical, and behavioral factors influencing myopia progression. The project’s ambitious goal is to transform how we understand, monitor, and treat myopia—turning personalized vision care into a reality.
**Mission confiée**:
Myopia is the most common refractive error observed in children and adults worldwide. This refractive disorder is generally due to an excessive elongation of the eye, which causes the image of a distant object to focus in front of the retina, resulting in a blurred perception in distance vision. The standard clinical management of myopia, in most cases, is solely focused on correcting the refractive error with single-vision glasses or contact lenses. The major challenge, however, is to develop therapeutic strategies to prevent and slow down myopia as early as possible in order to avoid high myopia and serious complications later in life.
Research has shown that focusing light signals in front of the retina helps in slowing down eye elongation, and therefore myopia progression. On this basis, new sophisticated optical glasses have emerged, with the dual objective of correcting myopia (by bringing the distant image onto the retina) and controlling myopia (by simultaneously creating a signal in front of the retina), slowing down the axial elongation of the eye characteristic of myopic progression. However, to date, these glasses are designed generically to treat all young people with progressive myopia, regardless of their individual profile, and show a large inter-individual variability in their effectiveness, which remains largely unexplained.
Your mission will be to contribute to the development of biomechanical models of the poly-articulated system comprised of the eye, the head and the neck. These models will be governed by physiologically plausible laws of motion, specifically for oculomotor convergence and eye-head coordination, which will be needed for the simulation of a variety of visual and behavioral tasks having an impact on myopia development on children (e.g. reading from a smartphone). These simulations will provide insights into how head and eye movements may influence optical performance and the progression of myopia, as well as optical and ergonomic effects of different lens designs for optimizing the fit, comfort, and efficacy of therapeutic eyewear.
Because of the high redundancy, geometrical complexity and interdependency of the eye-head-neck system, part of your work will focus on finding a trade-off among model complexity, model personalization and simulation predictiveness. This will probably require methodological developments relying on reduced-order modeling (probably via Artificial Intelligence) for very fast simulations, necessary for solving inverse problems that may arise for during personalization and inverse-kinematics contexts.
**Compétences**:
- ** Required**:
- M.Sc. or PhD in **biomedical engineering, applied mathematics, computer science**, or a related field.
- Strong background in **biomechanical simulation**of** multi-body systems**.
- Strong background with **numerical analysis**and** optimization techniques**.
- Proficiency in **scientific programming** (e.g., Python, C++).
- Communication skills for **team working**.
**Desirable**:
- Knowledge of the **eye-head-neck system**and its biomechanics.
- Knowledge of **machine learning techniques**.
- Experience in **collaborative research** or **interdisciplinary healthcare projects**.
**Avantages**:
- Subsidized meals
- Parti