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Forschungszentrum Jülich

PhD Position in Hybrid Electronic/Photonic Integrated Neuromorphic Computing Systems for Large-Scale Machine Learning Forschungszentrum Jülich GmbH in Germany

Degree Level

PhD

Field of study

Computer Science

Funding

EU-funded Doctoral Network PhD position. The role is classified as pay group 13 (75%) of TVöD-Bund, with an additional year-end bonus amounting to 75% of a monthly salary and capital-forming benefits. The position is initially fixed term for 3 years, with the prospect of longer-term employment.

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Country

Germany

University

Forschungszentrum Jülich

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Keywords

Computer Science
Signal Processing
Electrical Engineering
Materials Science
Physics
Electronics
ML
computational architecture

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About this position

PhD position at Forschungszentrum Jülich in the Peter Grünberg Institute – Neuromorphic Compute Nodes (PGI-14), working in the Adaptive In Memory Computing Group on hybrid electronic/photonic integrated neuromorphic computing systems for large-scale machine learning.

The project is part of the EU-funded MINDnet Doctoral Network, bringing together 15 PhD students across 7 universities, one research center, and two companies in eight EU countries. The research theme spans neuromorphic computing, analog signal processing, and applications in communication, sensing, geolocalization, space, and biomedical domains.

Research tasks include optimizing hybrid electrical-optical computing architectures, characterizing and modeling electronic and optical devices, developing hardware-aware machine learning models, designing hardware-efficient training methods, benchmarking against state-of-the-art studies, and performing numerical modeling and experimental validation of brain-inspired algorithms. The project also involves setting up and operating circuit-level measurement systems and data analysis workflows.

Applicants should have a master’s degree in electrical/electronic engineering, computer engineering, computer science, physics, or a related field. The post asks for experience with emerging memory devices, a strong electronics background, and familiarity with analog, digital, or mixed-signal circuit analysis and simulation tools such as SPICE, LTspice, Cadence, MATLAB, and Python. Strong communication and teamwork skills are required, along with English at CEFR B2 level or higher. Marie Skłodowska-Curie mobility rules apply, meaning applicants must not have spent more than 12 months in Germany during the 36 months before recruitment.

The position is based in Aachen, Germany, with secondments of about 3 months each at HPE Belgium (Brussel), SpiNNcloud Systems GmbH (Dresden), and Technical University Ilmenau. The appointment is initially for 3 years and is funded under TVöD-Bund pay group 13 (75%), including a year-end bonus and capital-forming benefits.

Applications are accepted via the online portal linked in the posting. The vacancy remains open until filled.

Funding details

EU-funded Doctoral Network PhD position. The role is classified as pay group 13 (75%) of TVöD-Bund, with an additional year-end bonus amounting to 75% of a monthly salary and capital-forming benefits. The position is initially fixed term for 3 years, with the prospect of longer-term employment.

What's required

Applicants must hold a master's degree in electrical/electronic engineering, computer engineering, computer science, physics, or a related field. Required experience includes emerging memory devices and a strong electronics background with analysis and simulation of analog, digital, or mixed-signal circuits using SPICE and related tools such as LTspice, Cadence, MATLAB, and Python. Excellent communication and teamwork skills are essential. Very good written and spoken English at least at CEFR B2 level is required, ideally supported by a language certificate. Due to Marie Skłodowska-Curie mobility rules, applicants must not have resided or carried out their main activity in Germany for more than 12 months in the 36 months before recruitment.

How to apply

Apply through the online application portal linked in the job posting. Review the application information and FAQ pages before submitting. For questions, use the provided contact form or career portal.

More information can be found here

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