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2026 offers

Probabilistic Non-Rigid Image Registration for Safe Brain Tumor Surgery

Generative Modeling for Efficient Exploration of Reactive Molecular Configuration Spaces

Automatic Detection of Meaning Misalignment in Dialogue for the Evaluation and Improvement of Conversational AI

Causal discovery and Information Theory for high-dimensional biological data

Rewriting Description Logic Queries into GQL

Machine-Learning for Antibody-Antigen Recognition: Models and Theory

Staff Scientist Position in AI
for Computational Biology of Cancer at Institut Curie

Evaluating Political Belief Formation in Human–LLM Interaction

AI-Driven Narrative Personalization for Effective Educational Communication

Learning to Choose: Adaptive Electronic-Structure Methods for Excited States in
Photocatalysts

Physics-Grounded World Models for Scalable, Efficient and Robust Robot Learning

Towards Explainable Foundation Models via Learned Neural Specifications

Discovery of novel mechanical metamaterials using generative AI

LT4NeuroAI: Developing Mathematical Learning Theory for State-Space Models used in NeuroAI

Caractérisation de la distribution dans l’espace latent des images normales pour améliorer la détection non supervisée d’anomalies

Optimal Transport, Latent Representations and Generative Models

A Study of the Implicit Bias in Deep Learning through a Higher-Order Analysis of the Loss

Performative Learning for Long-Term Trustworthy Machine Learning

Physics Informed Deep Learning for Non-Invasive Imaging Through Strongly Scattering Media

Task-Specific and Linguistically Motivated Evaluation for Multilingual NLP

Interpretable AI for unveiling distributed computations in the brain

Simulatable Physics-aware World Models

Doctor decision-making, practice styles, and patient-doctor match formation