Forschungszentrum Jülich
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PhD Position in Neuromorphic Computing for Gravitational Wave Detection Forschungszentrum Jülich GmbH in Germany
Degree Level
PhD
Field of study
Computer Science
Funding
Full funding availableCountry
Germany
University
Forschungszentrum Jülich

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About this position
Forschungszentrum Jülich GmbH is advertising a PhD position in Neuromorphic Computing for Gravitational Wave Detection at the Peter Grünberg Institute – Integrated Computing Architectures (PGI-4/ICA) in Jülich, Germany.
The project is part of a BMFTR-funded effort supporting the Einstein Telescope and focuses on developing a real-time processing architecture for noise mitigation in gravitational wave detection. The work combines neuromorphic computing, embedded AI, FPGA-based data processing, neural networks, and real-time signal processing for sensor-to-processing hardware interfaces.
Typical tasks include evaluating neural network types for efficient hardware implementation, designing an FPGA-optimized solution, performing device-aware training on simulated and measured datasets, validating the hardware interface, collaborating with project partners, and presenting/publishing research results.
Applicants should have a Master’s degree in electrical engineering, physics, computer science, or a related field, plus strong experience in embedded AI, neural network design/training, FPGA development or embedded hardware design (VHDL/Verilog or HLS), Python/C++, and signal processing. A very good command of English at B2 level or higher is required.
The position is initially for 3 years, classified as TVöD-Bund E13 (75%), with additional year-end bonus and capital-forming benefits. The post is open until filled. Apply online through the career portal; the posting also provides application information, FAQ, and contact details.
Funding details
Full funding including tuition fees and living expenses is available for this position. The scholarship covers all educational costs and provides a monthly stipend.
How to apply
Please submit your application including a cover letter, CV, academic transcripts, and contact information for two references. Applications should be sent via the online portal before the deadline.
More information can be found here
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