Postdoc: Data-driven approaches for designing next-generation spintronic information systems

Theoretical evaluation of the performance of nanoelectronic (especially spintronic) systems is essential for targeting the most suitable parameters to design real devices, determining their optimal operating points, and integrating them into information processing architectures. The classical approach is to use intensive numerical simulations, but their complexity usually prevents their exploitation in the analysis of complex nanotechnological information processing architectures. The first objective of this project will be to combine the expertise in spintronics and nanotechnology within the Institut Jean-Lamour (IJL, Nancy, France) and the skills in modeling complex systems of the LMOPS Laboratory (Metz, France) for the development of new methods based on the analysis of large volumes of data and statistical learning for the establishment of data-driven models for the prediction of the dynamic behavior of complex spintronic systems, more specifically systems currently studied at the Institut Jean-Lamour (IJL). The second objective will be to exploit these data-driven models for the analysis of spintronic architectures as building blocks of telecommunication networks. Duration of the project: 2 years.