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Modelling of magnetic and spin-based devices for memory and logic applications
PhD - Leuven | Just now
Join the innovation on next generation devices exploring magnetic properties from physics to circuit design
Magnetic and spin-based technologies attract considerable interest for many applications: non-volatile data storage, low-power majority gate logic, neuromorphic computing. These devices are promising alternatives to traditional semiconductor-based devices as they offer built-in memory effect, low power consumption, scalability, reconfigurability. Magnetic Random-Access Memories (MRAMs) have already emerged as a leading candidate for next generation non-volatile memories.
This PhD research addresses the modelling of magnetic and spin-based devices for design-technology co-optimization. The student will develop physics-based models suited for circuit simulations, calibrate the models on experimental data, and use them for memory and logic low level simulations. Based on data analysis, compact modelling, and circuit simulations, the candidate will provide further understanding of the impact of materials, devices structures and design choices on performance and will be involved in the innovation process to develop the next generation devices. She/He will work at the crossing point between technology development and design of new architectures, interacting with different specialists.
Metal-based spintronic devices can rely on a variety of operating principles : magnetization switching, domain wall motion, spin wave propagation. Magnetization switching can be current induced, voltage controlled, spin-hall effect assisted. The research will focus in a first phase on Voltage-Controlled Magnetic Anisotropy (VCMA), Spin-Orbit Torque (SOT) switching, VCMA+SOT, and domain wall based memories. Imec develops these devices integrated in CMOS technologies with leading edge 300mm/EUV tool sets.
Profile : You like physics and mathematical modelling. You are comfortable in programming. Background in digital logic and circuit simulations is a plus.
Required background: Physics, Electrical Engineering, or equivalent
Type of work: 80% modeling/simulation (device and circuit level) 10% experimental, 10% literature
Supervisor: Jo De Boeck
Daily advisor: Marie Garcia Bardon
The reference code for this position is 2021-022. Mention this reference code on your application form.