[PostDoc] Deep Learning for 4D lung MRI

Title: Post‑Doctoral Researcher – Evaluating Lung Function and Dynamics using Deep Learning Keywords: Machine Learning, Magnetic Resonance Imaging (MRI), Registration, Segmentation, Biomarker Discovery, Lung Dynamics, Respiratory Function Duration: 18 months Start Date: February 2026 (flexible) Institution: Université Paris-Saclay Host Laboratory: Laboratoire d’imagerie médicale multimodale (BioMaps) Collaboration: V|LF Spiro 3D European…

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[StageM2+PhD] Leveraging Domain Adaptation in Unsupervised Federated Learning

Duration: 6 monthsStart date: From February or March 2026Level: Master’s degree (M2 or equivalent) in Applied Mathematics, Computer ScienceAllowance: According to current French regulations (approximately €630/month)Location: LITIS, University of Rouen Normandy, Rouen, FranceKeywords: Federated Learning, Source-Free Domain Adaptation, Class Imbalance, Unsupervised Learning Context Federated learning (FL) enables models to learn from distributed datasets across diverse clients…

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[StageM2] Effets de phase géométrique en PolInSAR : Estimation de déphasage et géométrie Riemannienne

Contexte Le PolInSAR (Polarimetric Interferometric SAR) combine polarimétrie et interféro-métrie radar pour l’observation de la Terre [1]. Cette technique exploite la sensibilité polarimétrique aux mécanismes de diffusion et la sensibilité interférométrique à la structure verticale des cibles, permettant notamment d’estimer la hauteur et la biomasse forestière avec une large couverture…

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[StageM2+PhD] in Signal Processing: Time–Frequency Analysis

Duration: 6 monthsStart date: From February 2026Level: Master’s degree (M2 or equivalent) in Applied Mathematics, Signal or Image ProcessingAllowance: According to current French regulations (approximately €630/month)Location: IRIMAS Institute – IMTIS team, University of Haute-Alsace, Mulhouse, FranceKeywords: time–frequency analysis, frame theory, optimization, off-grid sparsity Context and Objectives This internship focuses on…

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[StagesM2] en vision par caméra à événements / Internships in event camera vision / Heudiasyc UTC Compiègne

Nous proposons 3 stages de Master liés à la vision événementielle / We propose 3 Master internships related to event vision Laboratoire : Heudiaysc UMR CNRS 7253 à Compiègne, équipe SyRI https://www.hds.utc.fr/recherche/equipes-de-recherche/syri-systemes-robotiques-en-interaction/ Sujet 1) : Réseaux de neurones légers pour la vision basée événementsPosition 1): Lightweight neural networks for event-based…

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[StageM2] MAPS-FM : Multi-Annotator-Aware Prostate Segmentation with Foundation Models for reliable and interpretable outcomes

Context Accurate segmentation of the prostate and its anatomical zones – Transitional Zone (TZ), Peripheral Zone (PZ), and the whole gland – from Magnetic Resonance (MR) images is essential for biopsy targeting, radiotherapy planning, and surgical decision-making. However, segmentation remains subjective: even experienced radiologists produce variable contours, particularly at the…

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[StageM2] MAPS-FM : Multi-Annotator-Aware Prostate Segmentation with Foundation Models for reliable and interpretable outcomes

Context Accurate segmentation of the prostate and its anatomical zones – Transitional Zone (TZ), Peripheral Zone (PZ), and the whole gland – from Magnetic Resonance (MR) images is essential for biopsy targeting, radiotherapy planning, and surgical decision-making. However, segmentation remains subjective: even experienced radiologists produce variable contours, particularly at the…

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[StageM2] Statistical Shape Models of the Lower Limb: Comparing Mesh Correspondence Methods 

Keywords: Medical Image Analysis, Statistical Shape Model, Mesh Correspondence, Artificial Intelligence, Multi-Object (tibia, muscle, skin) Born from the complementarity between the field of health and communication sciences, the LaTIM is a research lab which leads multidisciplinary research driven by scientists, engineers, and physicians from the University of Brest, IMT Atlantique,…

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