GLoW Project Seeks AI Researcher for Brain-Inspired Deep Learning

The interdisciplinary GLoW project, backed by an ERC Advanced grant, aims to explore brain-inspired cognitive architectures for more robust, flexible, and frugal cognition. It is based on the cognitive theory of the "global workspace": a large-scale system integrating and distributing information between specialized modules (perception, language, decision, action) to generate advanced forms of cognition. The project will directly implement the global workspace in deep learning models of increasing complexity and evaluate their correspondence with brain networks. This provides an explicit evaluation of this fundamental neurocognitive theory and pushes the limits of current systems toward a new generation of AI. The project seeks a candidate to develop an original line of research in bio-inspired Artificial Intelligence and deep learning. The candidate will participate in the design, programming, and evaluation of neural network architectures, integrating sensory and linguistic information. They will also use advanced AI models to enhance the decoding and understanding of brain activity. A Ph.D. in AI, computer science, deep learning, computational neuroscience, or a related field is required. Strong programming skills (e.g., MATLAB, Python) and experience with deep learning environments (PyTorch, TensorFlow, Keras, Jax...) are essential. Fluency in English is mandatory; no French knowledge is needed.