PhD in Hardware-Algorithm Co-Design: The Peter Grünberg Institute – Neuromorphic Software Ecosystems (PGI-15) is offering a PhD position focused on developing algorithms for hardware-algorithm co-design. This position leverages neuromorphic computing technologies and emphasizes collaboration and innovation in computing algorithms and architectures inspired by neuroscience.
PhD Scholarship Opportunity: Algorithms for Hardware-Algorithm Co-Design
Designation
PhD Candidate in Algorithms for Hardware-Algorithm Co-Design
| Details | Information |
|---|---|
| Research Area | Algorithms, Neuromorphic Computing, Hardware Design |
| Location | Aachen, Germany |
| Eligibility/Qualification | Master’s degree in Physics, Electrical/Electronic Engineering, Computer Science, Mathematics, or related field |
| Description | The research focuses on meta-optimization techniques for algorithm-hardware pairing to enhance efficiency and performance in computing applications. Candidates will work closely with both internal and external research partners, engage in publication opportunities, and have access to state-of-the-art facilities. |
| How to Apply | Interested candidates should apply through the provided application link by submitting necessary documentation as specified in the application process. Please refer to the FAQ section for additional tips. |
| Last Date to Apply | September 30, 2025 |
Detailed Description
The PGI-15 team works toward automating the algorithm-hardware co-design process, seeking innovative methods to improve efficiency and performance. The role involves developing meta-optimization methods and collaborating internationally to advance neuromorphic computing technologies.
Key Responsibilities:
- Develop and apply meta-optimization techniques.
- Collaborate with PGI-14 on next-generation analog circuits.
- Contribute to sparse auto-differentiation libraries.
- Publish research and present findings at international conferences.
- Mentor student projects.
Eligibility/Qualification
Candidates are expected to hold a Master’s degree in relevant fields and possess strong backgrounds in machine learning, especially in deep learning and optimization methods. Excellent coding skills, particularly in Python and proficiency with machine learning frameworks such as PyTorch or Jax, are essential.
How to Apply
Applications should be submitted via the designated application portal. Detailed guidelines for submission are available on the application page, along with answers to frequently asked questions.
Last Date to Apply
Applications will be accepted until September 30, 2025.
For more information and to apply, visit the official application page.
