PhD Position – Hybrid electronic/photonic integrated neuromorphic computing systems for large-s[...]

recruiting.fz-juelich.de - Jobboard; Aachen; Vor Ort; EUR 50.000 - 60.000; Vollzeit

Benefits dieser Stelle

30 days of annual leave

Flexible working hours

Training and networking opportunities

Support for international employees

Christmas bonus

Zusammenfassung

A leading research institution in Aachen seeks PhD candidates for a European Union-funded Doctoral Network project in neuromorphic computing. The role involves researching optimal computing architectures and developing algorithms while collaborating with an international team. A Master’s degree in engineering or related fields, along with an electronics background, is essential. The position offers flexible working options, a supportive environment, and a competitive salary package. Start date is anticipated between May and September 2026.

Qualifikationen

• You must not have resided in Germany for more than 12 months in the last 36 months.
• Experience in analysis and simulation of analog, digital or mixed-signal circuits.

Aufgaben

• Investigate optimal computing architectures for large-scale machine-learning workloads.
• Develop machine-learning models that incorporate device constraints.
• Conduct performance analysis against state-of-the-art studies.
• Design experimental systems for data analysis.

Kenntnisse

Electronics background

Communication skills

Teamwork

Experience with emerging memory devices

Strong English skills

Ausbildung

Master’s degree in electrical/electronic engineering, computer engineering, computer science, physics or related fields

Tools

LTspice

Cadence

MATLAB

Python

Jobbeschreibung

There exists a substantial gap between the computational abilities of modern computers and those of the brain. The new Peter Grünberg Institute – Neuromorphic Compute Nodes (PGI‑14) aims to close this gap and develop novel computing capabilities by incorporating some of the remarkable features found in biological brains. We aim to lower the energy consumption of today’s hardware while expanding our understanding of the fundamentals of computation. Practical application areas include AI and machine learning, intractable NP‑hard problems, scientific computing, and signal processing. We utilize novel technologies such as analog memristors combined with modern CMOS elements to build practical circuits and integrated chips for end‑to‑end demonstrations in the laboratory. The institute has close collaborations with the new Peter Grünberg Institute – Neuromorphic Software Ecosystem (PGI‑15) and with device, materials, circuit researchers and neuroscientists within other institutes at the Forschungszentrum Jülich.

Your Job

You will participate in an international team in an EU‑funded Doctoral Network project called MINDnet. The project consists of 15 PhD students at 7 universities, one research centre and two companies. The project partners from eight different EU countries will work on the overall theme of neuromorphic computing and analog signal processing, targeting communication, sensing, geolocalisation, space and biomedical applications.

This PhD project will take place at PGI‑14 Research Centre Jülich. Apart from the time at PGI‑14 there will be secondments of 3 months at HPE Belgium (Brussels), Spincloud Systems GmbH (Dresden) and Technical University Ilmenau. There will also be regular meetings with the other 14 PhD students in the doctoral network, including 4 training schools and two workshops.

As a participant of the project, you will become part of the group “Adaptive In‑Memory Computing Group” at PGI‑14.

Background MINDnet

The exponential surge in artificial intelligence, internet traffic and online services demands a revolutionary leap in devices, computing architecture and integration technologies. MINDnet will investigate neuromorphic computing as a promising solution, drawing inspiration from the brain’s powerful and energy‑efficient processing capabilities. It aims to address the challenge through holistic optimisation—from individual computing devices to the overall architecture—focusing on applications and training methods across multiple technological platforms including photonics, electronics and biological neurons.

Responsibilities and tasks

• Investigate and design optimal computing and communication architectures for hardware acceleration of large‑scale machine‑learning workloads
• Perform characterisation and modelling of electronic and optical devices
• Develop hardware‑aware machine‑learning models incorporating electronic and optical device constraints
• Design and implement hardware‑efficient training methodologies for machine‑learning systems
• Conduct comparative benchmarking and performance analysis against state‑of‑the‑art studies
• Perform numerical modelling and validation of brain‑inspired and neuromorphic algorithms
• Design, set up and operate experimental systems for circuit‑level measurements and data analysis

Your Profile

• IMPORTANT: You must not have resided or carried out your main activity in Germany for more than 12 months in the 36 months immediately before your recruitment date (mobility rules of the Marie Skłodowska‑Curie programme).
• Master’s degree in electrical/electronic engineering, computer engineering, computer science, physics or related fields
• Experience with emerging memory devices
• A strong electronics background, including experience in the analysis and simulation of analog, digital or mixed‑signal circuits, with tools such as LTspice, Cadence, MATLAB and Python
• Excellent communication skills and ability to work in a team are essential
• Strong English skills will be required for the international working environment

Further obligations

You are expected to travel to network partners on three assignments, each typically lasting 2–3 months. Additionally, you are expected to participate in outreach activities including, but not limited to, YouTube videos, social media updates, participation in public events and campaigns, and dissemination to popular press.

Our Offer

• Environment & Infrastructure: You will participate in a world‑leading, international research environment with state‑of‑the‑art equipment.
• Research & Team: Opportunity to work in the highly interdisciplinary field of neuromorphic and brain‑inspired computing, collaborating with physicists, neuroscientists, materials scientists and engineers.
• Work‑Life Balance: We offer flexible working hours to help you balance professional and personal life. Flexible working and location options are possible after consultation.
• Vacation: 30 days of annual leave and arrangement for bridging days (e.g., between Christmas and New Year’s Day).
• Knowledge & Development: Your professional development is important to us – we support you with training and networking opportunities specifically for doctoral candidates (JuDocS): https://go.fzj.de/JuDocs.
• Support for international employees: Our International Advisory Service eases the start for international employees.
• Fair Remuneration: Depending on your qualifications and assigned responsibilities, you will be classified according to pay group 13 (75%) of the TVöD‑Bund. Additionally, you will receive a special payment (“Christmas bonus”) amounting to 60% of one month’s salary. Details on the TVöD‑Bund collective agreement can be found on the BMI website.
• Perspective: The position is initially for a fixed term of 3 years but with prospect of longer‑term employment. Additional benefits are listed at https://go.fzj.de/benefits.

Diversity and inclusion

We welcome applications from people with diverse backgrounds, e.g. in terms of age, gender, disability, sexual orientation/identity and social, ethnic and religious origin. A diverse and inclusive working environment with equal opportunities in which everyone can realise their potential is important to us. Further information on diversity and equal opportunities: https://go.fzj.de/equality; and on the targeted promotion of women: https://go.fzj.de/womens-job-journey.

Place of employment

Aachen

Start for the grant

January 1, 2026.

Preferred start of employment

Between May and September 2026.

Funding

This project has received funding from the European Union’s Horizon 2020 Research and Innovation Programme under the Marie Skłodowska‑Curie Grant Agreement No. 101226674.

Application deadline

The position will be advertised until it has been successfully filled. We encourage you to submit your application as soon as possible.