Master Sciences cognitives - Parcours : Neurosciences Computationnelles et Intelligence Artificielle / Computational Neuroscience and Artificial Intelligence

General cog-SUP organization

The master’s student must register to one of the tracks. These tracks ensure the acquisition of genuine expertise in the concepts, methods, and techniques specific to each discipline, enhancing the clarity of skills associated with the diploma. The program establishes a common cultural foundation from the first year (M1) through a core curriculum and introductory courses to the different disciplines. In the second year (M2), the majority of courses are fully interdisciplinary and open to students from all tracks. Our goal is to cultivate cognitivists equipped with both robust disciplinary expertise and a broad interdisciplinary culture, essential elements for fostering meaningful collaboration across disciplines.

Specific to the track Computational Neuroscience and Artificial Intelligence

Training
The Computational Neuroscience and Artificial Intelligence (CNIA) program provides comprehensive interdisciplinary training at the intersection of cognitive sciences, computational neuroscience, and artificial intelligence. By combining rigorous theoretical approaches and advanced digital tools, this program aims to develop experts capable of modeling and analyzing the natural and artificial mechanisms of cognition.

Prerequisites
This program is designed for students with a dual skillset or strong interest in complementary disciplines. Ideal profiles include:
– Students in mathematics or computer science with an interest for neurosciences, psychology or biology.
– Or conversely, students in neurosciences, psychology or biology with training in mathematical and computational tools.

Career Opportunities
Graduates of the Computational Neuroscience and AI program will be equipped for diverse careers in:
– Academic and applied research (computational neuroscience, AI, cognition).
– Tech industries (AI, data processing, digital health).
– Expertise in technology and data ethics.