PhD position in Photonic Reservoir Computing (EU Researcher) (f/m/d)

In the Department of Physics in the group Theorectical Physics II at the Technische Universität Ilmenau (Germany) is a vacancy for a

PhD position in Photonic Reservoir Computing (EU Researcher) (f/m/d)

to promote their own academic qualifications within the meaning of Section 2 (1) of the German Academic Fixed-Term Contract Act (Wissenschaftszeitvertragsgesetz) starting from July 2026.

The Theoretical Physics Group at the Technical University of Ilmenau is seeking a candidate for a PhD position to research adaptability and memory in physical reservoir computing systems. The PhD student 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.

Apart from the time at TU Ilmenau there will be secondments of minimum 3 months at HP Enterprise (Belgium) to study large-scale neuromorphic chips, at Technical University of Denmark (Kopenhagen) to study optical ring resonators, and University College London (UK) to study optical excitation in memristors. 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, the PhD student will become part of a team at TU Ilmenau with expertise in modelling photonic devices and physical reservoir computing systems. The activities within the project will benefit from synergies with other projects in the group as well as with other activities at the department. The main supervisor will be Prof. Dr. Kathy Lüdge from TU Ilmenau.

Your tasks

The position includes the following responsibilities:

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. Photonics is a promising platform however it suffers from relatively energy-inefficient nonlinearities, e.g. compared to electronics. Resonant structures can enhance the nonlinear interaction and therefore increase the energy efficiency of the process.

This PhD project aims to get an in-depth analysis of the memory and adaptability in physical reservoir computers by modelling and nonlinear dynamics analysis of complex laser systems .

The project will consist among others of the following tasks:

• Bifurcation analysis of the optical devices used as computing units
• Investigate ML tasks where short-term memory is required, i.e. time series prediction or speech recognition, with respect to the bifurcation structure of the underlying optical networks
• predict good operation regions with augmented memory using input and output delay.

The doctoral candidate (DC) is expected to travel to network partners under three secondments for a typical total duration of 2-3 months. Additionally, the DC is 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.

Your profile

For being part of the selection process is needed:

You must have an academic level equivalent to a two-year master's degree in physics or related disciplines.

Following competences are desirable:

• Experience in programming with python or C++
• Basic knowledge in laser modelling
• Basic knowledge in nonlinear dynamics
• Good communication skills in English

Please provide evidence of the qualifications required for the job by certificates and references.

The position is not suitable for part-time employment.

Candidates can be of any nationality and must not have resided or carried out his/her main activity (work, studies etc) in Germany for more than 12 months in the 36 months immediately before their date of recruitment. The candidate must not be already in possession of a doctoral degree at the date of the recruitment. Researchers who have successfully defended their doctoral thesis but have not yet formally been awarded the doctoral degree will not be considered eligible. The eligibility of the researcher will be determined at the date of their first recruitment in the action. Eligible applicants will undergo a pre-selection evaluation based on the CV, experience and skills. Short-listed applicants will be invited for an interview with the evaluation committee members, potentially by online conferencing.

What we offer you:

• vacation entitlement of 30 days in the calendar year and additional days off on 24 / 31 December
• family-friendly, flexible working time model
• wide range of individual training opportunities
• extensive health and sports programs
• respectful working environment at a renowned university

The university stands in the fields of technology, mathematics and natural sciences, business and media for teaching and research at the highest level. It attaches particular importance to innovativ teaching and interdisciplinary. It identifies with Humboldt's ideals and pursues the vision of a cosmopolitan campus family.

Technische Universität llmenau is holder of the „TOTAL E-Quality“ distinction and emphasizes gendered quality.

Severely disabled applicants with essentially identical professional suitability will be preferentially selected.

ID Number: 100/2025
application deadline: 15.03.2026