Computational Modelling For Medical Device Optimization And Patient-Specific Hemodynamics H/F - INRIA

A propos d'Inria

Inria est l'institut national de recherche dédié aux sciences et technologies du numérique. Il emploie 2600 personnes. Ses 215 équipes-projets agiles, en général communes avec des partenaires académiques, impliquent plus de 3900 scientifiques pour relever les défis du numérique, souvent à l'interface d'autres disciplines. L'institut fait appel à de nombreux talents dans plus d'une quarantaine de métiers différents. 900 personnels d'appui à la recherche et à l'innovation contribuent à faire émerger et grandir des projets scientifiques ou entrepreneuriaux qui impactent le monde. Inria travaille avec de nombreuses entreprises et a accompagné la création de plus de 200 start-up. L'institut s'eorce ainsi de répondre aux enjeux de la transformation numérique de la science, de la société et de l'économie.Computational Modelling for Medical Device Optimization and Patient-Specific Hemodynamics
Le descriptif de l'offre ci-dessous est en Anglais
Type de contrat : Stage

Contrat renouvelable : Oui

Niveau de diplôme exigé : Bac +4 ou équivalent

Fonction : Stagiaire de la recherche

A propos du centre ou de la direction fonctionnelle

The Inria Saclay-Île-de-France Research Centre was established in 2008. It has developed as part of the Saclay site in partnership withParis-Saclay Universityand with theInstitut Polytechnique de Paris.

The centre has40, 27 of which operate jointly with Paris-Saclay University and the Institut Polytechnique de Paris; Its activities occupy over 600 people, scientists and research and innovation support staff, including 44 different nationalities.

Contexte et atouts du poste

The project includes collaboration between Marie Lannelongue Hospital and Inria team SIMBIOTX. It is part of the European project MoDeLLiver. The internship will be co-supervised by Irene Vignon-Clémentel (Directrice de recherche) and Pavlos Varsos (PhD student).

Mission confiée

Context:

This internship involves two complementary research tasks, both at the interface of computational hemodynamics, medical device design, and patient-specific cardiovascular modelling.

The first objective is to support the optimization of a double-flow cannula used in a portable artificial lung device intended for patients with end-stage lung failure. A numerical workflow is currently being developed, ranging from analytical flow equations and experimental characterization to full 3D CFD simulations. The goal is to build a parametrizable model enabling design optimization and performance prediction. Validation against existing experimental measurements will be performed before proposing and evaluating new cannula geometries.

The second objective refers to the contribution to the development of a reduced-order modeling pipeline for surgical planning in pulmonary arterial hypertension, a life-threatening pediatric disease. The workflow includes medical image-based vascular reconstruction, CFD simulations using clinical data, centerline extraction, and 0D reduced-order model construction.

Objectives:

- Develop and validate a parametrized CFD-based model of blood flow within a double-flow cannula.
- Evaluate new cannula designs to improve flow efficiency and pressure performance.
- Build a pipeline for patient-specific vascular modeling including:
- Image-based geometry reconstruction
- Flow simulation using clinical measurements
- Centerline extraction and morphological characterization
- Reduced-order hemodynamic model construction

Principales activités

Main tasks:

- Implement and validate CFD simulations of current cannula designs.
- Propose geometric modifications and assess their impact on flow performance.
- Reconstruct patient-specific vascular geometries from medical imaging data.
- Build and test reduced-order models.

Main tools:

- Software for segmentation and CFD
- CAD tools for geometry modification
- Python
- Numerical methods for cardiovascular modelling

Compétences

Technical skills:

- Fluid mechanics and basic understanding of cardiovascular flows
- CAD software (SolidWorks, Blender, etc.)
- CFD tools (OpenFOAM, ANSYS Fluent, SimVascular, etc.)
- Medical imaging segmentation (Slicer, etc.)
- Python for data processing and automation
- (Optional but appreciated) Experience with reduced-order modeling, numerical methods, or machine learning

Communication skills:

- English (fluent)
- Communicate scientific content orally to a reduced audience.

Misc.:

- Motivation to work on both medical device development and patient-specific modeling
- Team work and autonomy

Avantages

- Partial reimbursement of public transport costs
- Leave
- 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