A post-doctoral position is available at Université Côte d’Azur!
« Design and implementation of a brain-inspired embedded multimodal model applied to a nonlinear photonics application »
Artificial Intelligence, Multimodal Unsupervised learning, Brain-inspired methods, Nonlinear Photonics
Multi modal sensing is key to how the human brain processes incoming information and adapts to the external world. In the AI realm, recent research at the LEAT has shown how sensory modalities can be merged to enhance the quality of the classification or the reconstruction of signals in a noisy environment using brain-inspired learning methods. Within the EDGE team at LEAT and in collaboration with the “Complex photonic materials and systems” at Institut de Physique de Nice, the applicant will design, implement and assess the performance of advanced learning methods taylored towards the realization of high performance complex photonic sensors.
laurent.rodriguez at univ-cotedazur.fr
stephane.barland at univ-cotedazur.fr