# PhD Position – Hybrid electronic/photonic integrated neuromorphic computing systems for large-scale machine learning

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), as well as 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 Ph.D. students at 7 universities, one research center and two companies. The project has partners from eight different EU countries. All 15 Ph.D. 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 Ph.D. 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), SpiNNcloud Systems GmbH (Dresden), and Technical University Ilmenau (Germany). There will also be regular meetings with the other 14 Ph.D. 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. As digital computing struggles to keep up with the growing demand, in MINDnet will investigate 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.

**Responsibilities and tasks**

This PhD project aims to (1) optimize the design of hybrid electrical–optical computing architectures and (2) develop learning rules that are both technology-feasible and well-suited for machine-learning workloads.

The project will consist among others of the following tasks:

- 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

## Your Profile

- **Important:** Due to the mobility rules of the Marie Skłodowska-Curie program, 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 their recruitment date
- 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
- Very good command of written and spoken English with extensive vocabulary is required for the international working environment (at least B2 level according to the [CEFR](https://go.fzj.de/languagerequirements)), ideally supported by a certificate confirming the language level

**Further obligations**

You are expected to travel to network partners under three secondments for a typical total duration of 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, as well as dissemination to popular press.

## Our Benefits for You

We work on the very latest issues that impact our society and are offering you the chance to actively help in shaping the change! We support you in your work with:

- **Research & Infrastructure:** You will participate in a world-leading international research environment with state-of-the-art equipment
- **Team & Environment:** Opportunity to work in the highly interdisciplinary and exciting 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 your professional and personal life. You also have the option of flexible working (in terms of location), which is generally possible after consultation and in line with upcoming tasks and (on-site) appointments
- **Annual Leave:** You get 30 days of annual leave
- **Knowledge & Development:** Your professional development is important to us – we support you specifically and individually e.g., through training and networking opportunities specifically for doctoral candidates [(JuDocS)](https://go.fzj.de/JuDocs)
- **Fair remuneration:** Depending on your qualifications and assigned responsibilities, you will be classified according to pay group 13 (75%) of the TVöD-Bund. In addition to the basic salary, there is an additional year-end bonus under the collective pay agreement amounting to 75% of a monthly salary, as well as capital-forming benefits. All information about the TVöD-Bund collective agreement can be found on the [BMI website](https://go.fzj.de/bmi.tvoed) (pay scale table on page 66 ff. of the PDF download)
- **Perspective:** The position is initially for a fixed term of 3 years but with the prospect of longer-term employment
- **Support for international employees:** Our International Advisory Service makes it easier for international employees to get started

In addition to exciting tasks and a collegial working environment, we offer you much more: [https://go.fzj.de/benefits](https://go.fzj.de/benefits)

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 realize their potential is important to us.

The following links provide further information on diversity and equal opportunities: [https://go.fzj.de/equality](https://go.fzj.de/equality) and on specific support options: [https://go.fzj.de/womens-job-journey](https://go.fzj.de/womens-job-journey)

**Place of Employment:** Aachen

**Start Date:**To the next possible date

**Salary:** Pay group 13 (75%) TVöD-Bund

**Application Deadline:** The position will be published until it is successfully filled.

[Application Process](https://go.fzj.de/ApplicationInformation) [FAQ](https://go.fzj.de/FAQ_eng) [Contact form](mailto:karriere@fz-juelich.de?subject=Query%20about%202026D-0504%20PhD%20Position%20%E2%80%93%20Hybrid%20electronic/photonic%20integrated%20neuromorphic%20computing%20systems%20for%20large-scale%20machine%20learning)

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