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Electrical Engineering and Physics● OpenOpen until filledPreview

PhD Position - Neuromorphic Computing in Gravitational Wave Detection

Develop real-time neuromorphic computing architectures to enhance gravitational wave detection sensitivity for the Einstein Telescope.

Best for:Best for researchers with a background in embedded AI, FPGA development, and signal processing interested in experimental physics.

Forschungszentrum Jülich · Jülich, Germany · R1 · First-stage researcher
More professors at Forschungszentrum Jülich
Neuromorphic ComputingGravitational Wave DetectionFPGA DevelopmentEmbedded AISignal ProcessingNoise Mitigation
Deadline
Until filled
rolling
Funding
Salaried
Pay group 13 (75%) TVöD-Bund
Start date
flexible
Fixed-term
Location
Jülich
Germany

Overview

The Peter Grünberg Institute at Forschungszentrum Jülich is seeking a doctoral researcher to join an interdisciplinary project focused on noise mitigation for the Einstein Telescope. The successful candidate will design and implement FPGA-based neuromorphic computing systems to process seismic sensor data in real-time. This role involves bridging novel hardware architectures with practical applications in experimental physics. The researcher will collaborate with international partners and contribute to the development of next-generation gravitational wave detection technologies.

Neuromorphic ComputingFPGAEinstein TelescopeEmbedded AISignal ProcessingPhysicsHardware Design

What you'll do

  • Evaluate and select neural network architectures suitable for efficient hardware implementation.
  • Develop and optimize FPGA-based designs for real-time data processing.
  • Conduct device-aware training using both simulated and measured datasets.
  • Validate the complete hardware interface between sensors and processing units.
  • Collaborate effectively with internal project teams and international research partners.
  • Present research findings at scientific conferences and publish in peer-reviewed journals.

Requirements

Degree required: Master’s degree in electrical engineering, physics, computer science, or a related field.

Degree offered: PhD

Language: English; at least B2 level according to CEFR.

Instruction: English

Required skills
  • Strong academic background in embedded AI and neural network design.
  • Practical experience in FPGA development or embedded hardware design.
  • Proficiency in HDL (VHDL/Verilog) or high-level synthesis (HLS) tools.
  • Programming proficiency in Python or C++ for algorithm development and data analysis.
  • Experience with real-time signal processing, including time-series data and filtering.
  • Foundational knowledge of experimental physics or sensor systems.
Nice to have
Experience with noise mitigation strategies in complex measurement environments.Familiarity with feature extraction techniques.
Eligibility
  • Applicants must hold a Master's degree in a relevant field.

Funding & terms

Type
Salaried
Amount
Pay group 13 (75%) TVöD-Bund
Duration
3 years
Programme
BMFTR
BMFTR

How to apply

Interested candidates should apply through the official career portal. Ensure all required documents are prepared according to the instructions provided on the Forschungszentrum Jülich website.

Documents required
  • CV
  • Cover letter
  • Academic transcripts
  • Language proficiency certificate
↗Apply on site

Contact

Lab
Integrated Computing Architectures (PGI-4/ICA)
Forschungszentrum Jülich
Germany
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