CS27 - Bac +5- Data Scientist – Estimation en temps réel de la demande attentionnelle induite lors d’une situation de conduite (H/F)
Core
Develop AI models to estimate real-time attentional demand induced by driving scenarios using vehicle, infrastructure, and sensor data.
Role type
Research Data Scientist (Cognitive Science & AI)
Builds
Real-time attention estimation models for driving scenes
Domain
Automotive / Cognitive Science / Machine Learning
Deliverable
production ML models
Required skills
Python, PyTorch, TensorFlow, HuggingFace, GenAI tools (LLM APIs, embeddings, LangChain, ChromaDB), data analysis, scientific literature review
Preferred skills
Knowledge of human behavior and cognitive states, automotive industry interest
Technologies
Python, PyTorch, TensorFlow, HuggingFace, Git, LLM APIs, LangChain, ChromaDB
Responsibilities
Define metrics for characterizing attentional demand in driving scenes, search and analyze public/internal datasets, implement and evaluate AI models for scene detection and temporal dynamics, validate model efficiency on simulators or real conditions
Seniority
Junior (Bac+5 student/intern)
