Doctoral Researcher

**Job Description**
This doctoral research position focuses on automating the co-design of algorithms and hardware through the development and application of meta-optimization techniques. The project aims to identify optimal algorithm-hardware pairs, extending previous successes in digital neuromorphic hardware to next-generation analog circuits and memristive devices. The goal is to train systems that leverage the intrinsic non-linear dynamics of these devices to achieve complex, energy-efficient learning tasks.

**Skills & Abilities**
� Strong background in machine learning, particularly deep learning and optimization methods
� Excellent coding skills, particularly in Python and machine learning frameworks (PyTorch or Jax)
� The ability for creative and analytical thinking across discipline boundaries and abstraction levels
� Knowledge in integrated circuit design, testing and simulation using Cadence is a plus
� Knowledge of evolutionary optimization methods is a plus
� Very good communication skills in English, both spoken and written

**Qualifications**
Required Degree(s) in:
� Physics
� Electrical/Electronic Engineering
� Computer Science
� Mathematics
� Related field

**Experience**
Other:
� Strong background in machine learning, particularly deep learning and optimization methods
� Excellent coding skills, particularly in Python and machine learning frameworks (PyTorch or Jax)
� Ability for creative and analytical thinking across discipline boundaries and abstraction levels
� Knowledge in integrated circuit design, testing and simulation using Cadence (plus)
� Knowledge of evolutionary optimization methods (plus)
� Very good communication skills in English (spoken and written)

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