Research Associate in Learning Algorithms and Simulation for Spintronics Devices

Join our team as a Research Associate in Learning Algorithms and Simulation for Spintronics Devices. This role involves developing neural network models informed by experimental and simulated skyrmionic device behavior. You will design and implement hardware-aware training workflows in modern machine learning frameworks and explore innovative learning methods suitable for neuromorphic hardware. Candidates should have a PhD or be near submission in relevant fields, with strong experience in neural networks and machine learning. We value diverse perspectives and encourage applications from individuals with varied backgrounds.