PhD Position in Neuromorphic Computing with Memristors

Vor 5 Tagen

Aachen, Nordrhein-Westfalen, Deutschland Forschungszentrum Jülich Vollzeit
Your Job:

We are seeking a highly motivated doctoral researcher to explore and implement hybrid CMOS-memristor spiking neural networks, focusing on optimal neural architectures and their complexity-performance tradeoff in task-specific hardware designs.

  • Develop circuit-plausible training/inference algorithms and analyze them using hardware-aware simulations.
  • Iterate algorithm-circuit co-designs and quantify improved schemes, comparing and benchmarking them to competing approaches.
  • Support printed circuit board design and tape-out of integrated circuits.
  • Set up experimental systems for memristive circuit measurements and experimental data analysis.
  • Collaborate with cross-disciplinary experts in neuroscience and device physics.
Your Profile:

We are looking for a candidate with a Master's degree in electrical/electronic engineering, computer engineering, computer science, or a related field. Strong skills in mixed-signal circuit designs, simulation, and circuit layout tools are essential. Experience in neuromorphic computation or machine learning is a plus.

  • Background in device physics and analog or mixed-signal circuit designs.
  • Strong skill in mixed-signal circuit designs and simulation.
  • Skills in circuit layout tools and electrical measurements.
  • Interest and background in neuromorphic computation or machine learning.
  • Excellent communication skills and ability to work in a team.
Our Offer:

We offer a world-leading, international research environment with state-of-the-art equipment. You will have the opportunity to work in the highly interdisciplinary and exciting field of neuromorphic and brain-inspired computing, collaborating with physicists, neuroscientists, materials scientists, and engineers.

  • A world-leading, international research environment with state-of-the-art equipment.
  • Opportunity to work in the highly interdisciplinary and exciting field of neuromorphic and brain-inspired computing.
  • Flexible working arrangements, including the possibility of working from home.
  • 30 days of annual leave and an arrangement for bridging days.
  • Further development of your personal strengths through an extensive range of training courses and networking opportunities.

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