PhD Position – Algorithm-Circuit Codesign for Neuromorphic Computing with Memristors

Your Job:

We are looking for a doctoral researcher who will explore and implement hybrid CMOS-memristor spiking neural networks, exploiting optimal neural architectures (e.g. analyzing the complexity-and-performance tradeoff in different neuron models, dendritic compartments, etc.) in task-specific hardware designs, for both training and inference for identifying complex sequential patterns. The researcher will:

• develop circuit-plausible training/inference algorithms and analyze with hardware-aware simulations (e.g. LTspice and Cadence Spetre)
  
• iterate algorithm-circuit co-designs and quantify improved schemes, compare and benchmark to competing approaches
  
• support printed circuit board design and tape-out of integrated circuits (e.g. Altium Designer / Cadence Virtuoso)
  
• set up experimental systems for memristive circuit measurements and experimental data analysis
  
• interact with cross-disciplinary experts (e.g. neuroscientists and device physicists)

Your Profile:

• Master’s degree in electrical/electronic engineering, computer engineering, computer science, or related fields
  
• Background in device physics and analog or mixed-signal circuit designs
  
• Strong skill in mixed-signal circuit designs (active filter circuits, ADC, …) and simulation (SPICE, Cadence Spectre) is a must.
  
• Skills in circuit layout tools, such as Altium Designer (printed circuit board) and Cadence Virtuoso (integrated circuits)
  
• Skills in setting electrical measurements and analysis
  
• Interest and background in neuromorphic computation or machine learning is a plus
  
• Coursework and experience in machine learning and spiking neural networks is desired
  
• Excellent communication skills and ability to work in a team are essential.
  
• Strong English skills will be required for the international working environment

Our Offer:

We work on cutting-edge research topics with a high potential to positively impact society. We offer ideal conditions for you to complete your doctoral degree:

• 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, collaborating with physicists, neuroscientists, materials scientists, and engineers
  
• Flexible working arrangements e.g. working from home
  
• 30 days of annual leave as well as an arrangement for bridging days (e.g. between Christmas and New Year’s Day)
  
• Further development of your personal strengths, e.g. through an extensive range of training courses; a structured program of continuing education and networking opportunities specifically for doctoral researchers via JuDocS, the Jülich Center for Doctoral Researchers and Supervisors: https://www.fz-juelich.de/judocs
  
• Targeted services for international employees, e.g. through our International Advisory Service
  

In addition to exciting tasks and the collaborative working atmosphere at Jülich, we have a lot more to offer: https://go.fzj.de/benefits

Place of employment: Aachen

The position is initially for a fixed term of 3 years but with the prospect of longer-term employment. The salary is in line with pay group 13 (75%) of the Collective Agreement for the Public Service (TVöD-Bund). In addition, an annual special payment is granted (“Christmas payment”), which amounts to 60 % of the monthly salary. Further information on doctoral degrees at Forschungszentrum Jülich (including its various branch offices) is available at https://www.fz-juelich.de/en/careers/phd

More information about the PGI-14, you find here: https://www.fz-juelich.de/en/pgi/pgi-14

We particularly welcome applications from people from a diverse range of backgrounds (e.g. regardless of age, gender, disabilities, sexual orientation/identity, as well as social, ethnic, and religious background). We strive to offer a diverse and inclusive working environment in which people enjoy equal opportunities and are able to fulfill their potential.