Scientific background

Successes in deep learning show that the paradigm of neuromorphic computing is very attractive. However, current technology is based on the Turing/von Neumann architecture, requiring extensive communication and an excessive amount of energy for computing. The human brain performs pattern recognition tasks with a fraction of the power needed by supercomputers for similar tasks. In this multidisciplinary project, new (memristic) materials and architectures for neuromorphic computing will be investigated in order to develop materials that can learn.

The scientific aim of MANIC is to synthesize materials that can function as networks of neurons and synapses by integrating conductivity, plasticity and self-organization.

Training

MANIC’s training mission is to recruit fifteen Early Stage Researchers (ESRs) and provide them with the best possible research, academic and professional competencies, empowering them to become the next generation of European experts who take a leading research position in materials for cognitive applications. The MANIC training programme is thus designed to provide multidisciplinary training at the interface of chemistry, materials science, physics, computer science, mathematics and engineering with the aim of opening up new approaches in the field of neuromorphic computing. The overall ambition is that all participating Early Stage Researchers will gain knowledge in these disciplines.

MANIC aims to achieve this through an advanced interdisciplinary and intersectoral research training programme, extended with the development of both generic academic and transferable skills and career guidance. Moreover, each Early Stage Researcher will spend at least one month in the private sector in order to acquire specific skills in industrial research and management. Exposure of Early Stage Researchers to the private sector will enhance their capacity to understand industrial R&D strategies and will endow them with a more accurate sense of business requirements.