PhD Position – Hybrid electronic​/photonic integrated neuromorphic computing systems

Overview

Organisation/Company:
Forschungszentrum Jülich

Department:
Neuromorphic Compute Nodes (PGI-14)

Research Field:
Engineering >
Electrical engineering

Researcher Profile:
First Stage Researcher (R1)

Positions:
PhD Positions

Final date to receive applications: 30 Mar 2026 - 23:59 (Europe/Berlin)

Country:
Germany

Type of

Contract:

Temporary

Job Status:
Full-time

Hours Per Week: 39

Offer Starting Date: 1 Jul 2026

Is the job funded through the EU Research Framework Programme? Horizon Europe - MSCA

Grant Agreement Number:

Is the Job related to staff position within a Research Infrastructure? No

Area of research:
PHD Thesis

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 center and two companies. The project has partners from eight different EU countries. All 15 PhD projects are within the overall theme of neuromorphic computing and analog signal processing, targeting applications in the fields of communication, sensing, geolocalization, space and biomedical.

This PhD project will take place at PGI-14 Research Center Jülich. Apart from the time at PGI-14 there will be secondments of 3 months at HPE Belgium (Brussel), 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 (AI), internet traffic, and online services demands a revolutionary leap in devices, computing architecture, and integration technologies. MINDnet investigates neuromorphic computing as a promising solution to support such a demand by getting inspired by the brain’s powerful and energy-efficient processing capabilities. MINDnet aims at addressing the challenge through a holistic optimization - from individual computing devices to the overall architecture, including a focus on applications, and training methods - across multiple technological platforms - photonics, electronics, biological neurons.

• Investigate and design optimal computing and communication architectures for hardware acceleration of large-scale machine learning workloads
• Perform characterization and modeling 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 modeling and validation of brain-inspired and neuromorphic algorithms
• Design, set up, and operate experimental systems for circuit-level measurements and data analysis

• IMPORTANT:
  You must not have resided or carried out your main activity (work, studies, etc.) in Germany for more than 12 months in the 36 months immediately before your recruitment date (mobility rules of the Marie Skłodowska-Curie program)
• Masters 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, including SPICE and related tools (LTspice, Cadence, MATLAB, Python)
• Excellent communication skills and ability to work in a team are essential
• Strong English skills will be required for the international working environment

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, You Tube videos, social media updates, participation in public events and campaigns, as well as dissemination to popular press.

We work on cutting-edge research topics with a high potential to positively…