Phd Position

The Peter Grünberg Institute - Neuromorphic Software Ecosystems (PGI-15) led by Prof. Dr. Emre Neftci explores neuromorphic computing technologies that learn and work like the brain. Our research team designs computing algorithms and architectures from the perspective of neuroscience and their physical realizations in dedicated circuits and devices. Applications of our research are targeted to improve computing in computer vision, autonomous control, data processing in mobile devices, and scientific data analysis.

**Your Job**:
The conventional, manual co-design of algorithms and hardware is slow and inefficient. Our group develops methods and tools to automate the co-design process. The core of this project is the development of meta-optimization techniques that can automatically search for the best algorithm-hardware pair for a given problem.
While we have a history of success in optimizing digital neuromorphic hardware, this project will push into next-generation analog circuits and memristive devices, in collaboration with PGI-14. The goal is to train a system that leverages the intrinsic non-linear dynamics of these devices to perform complex learning tasks with extreme energy efficiency.

Your Job:

- Tackle the challenge of computationally expensive meta-optimization procedures by developing and using dedicated tools and processors
- Contribute to our sparse auto-differentiation libraries to accelerate the training of state-space models
- Collaborate closely with our internal partners at PGI-14 (Neuromorphic Hardware Nodes) and international academic and industry partners
- Publish research articles and regular participation in top international conferences to present your work
- Participate in yearly retreats organized by the doctoral network participants
- Support the dissemination of software tools and concepts
- Supervise student projects and BSc/MSc theses

**Your Profile**:

- Master’s degree in physics, electrical/electronic engineering, computer science, mathematics, or a related field
- 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. PGI-15 offers an English-speaking environment; therefore, German language skills are not required

**Our Offer**:
We work on the very latest issues that impact our society and are offering you the chance to actively help in shaping the change We support you in your work with:

- TEAM & ENVIRONMENT: You will work in a motivated team with an international and interdisciplinary focus - at one of the largest research institutions in Europe
- RESEARCH & INFRASTRUCTURE: You will have access to excellent scientific and technical facilities with state-of-the-art experimental equipment for your work in an international research environment and versatile opportunities to grow as a curious researcher. You will cooperate with researchers at the following institutes: Neuromorphic Hardware Nodes (PGI-14), Electronics Materials (PGI-7), the Institute of Neuroscience and Medicine - Computational and Systems Neuroscience (INM-6), The Jülich Supercomputer Center (JSC) and the Faculty of Electrical Engineering and Information Technology at RWTH Aachen.
- ENROLLMENT: The student will be enrolled in the PhD program of the department of Electrical Engineering and Information Technology, RWTH Aachen
- LEAVE: You will receive 30 days of leave plus additional days off (e.g. between Christmas and New Year's Day)
- SUPPORT FOR INTERNATIONAL EMPLOYEES: Our International Advisory Service makes it easier for international employees to get started

PERSPECTIVE: The position is initially for a fixed term of 3 years but with the prospect of longer-term employment. Let's use this time to find out how well we fit togetherPlace of employment: Aachen