A vacancy is available tojoin an international team working on an EU-funded doctoral network project called MINDnet. The project consists of 15 doctoral students from seven universities, one research centre and two companies. It has partners from eight EU countries. The 15 doctoral projects focus on neuromorphic computing and analogue signal processing, with applications in the fields of communication, detection, geolocation, space and biomedicine.
This doctoral project will be carried out at the PGI-14 Research Centre in Jülich. In addition to your stay at PGI-14, you will spend three months at Albira Tech SL (Barcelona, Spain), Graz University of Technology (Austria) and the University of Trento (Italy). You will also meet regularly with the other 14 doctoral students in the doctoral network, including four training centres and two workshops. As a participant in the project, you will be part of the “Computing in Dynamic Systems” group at PGI-14.
Background of MINDnet:
The exponential growth of artificial intelligence (AI), internet traffic and online services demands a revolutionary leap in devices, computing architecture and integration technologies. While digital computing struggles to meet the growing demand, MINDnet will investigate neuromorphic computing as a promising solution to meet this demand, drawing inspiration from the powerful and efficient processing capabilities of the brain. MINDnet seeks to address this challenge through holistic optimisation, from individual computing devices to overall architecture, with a focus on applications and training methods, across multiple technology platforms: photonics, electronics and biological neurons.
Responsibilities and tasks:
This PhD project aims to develop, verify and compare learning rules in complex spike neuron networks in the field of geolocation.
- Construction of a simulation model for complex neural networks with topologies close to neuroscience models
- Analysing dynamic states of complex neural networks with respect to network topology and neural parameters.
- Develop learning rules considering the strong non-linearities of neurons
- Identify suitable application tasks in the field of geolocation and optimise the network and learning rules accordingly.
- Design, configure, and operate experimental systems for circuit-level measurements and data analysis.
Requirements:
- Master’s degree in electrical/electronic engineering, computer engineering, computer science, physics or related fields.
- Courses in algorithms, computational complexity theory, and information theory
- Relevant courses and experience in state-of-the-art neural networks and statistics.
- A strong background in electronics, including experience in the analysis and simulation of analogue, digital or mixed-signal circuits, including SPICE and related tools (LTspice, Cadence, MATLAB, Python).
- Excellent communication skills and the ability to work in a team are essential.
- Strong English skills will be required for the international work environment.
Benefits:
- Depending on your qualifications and assigned responsibilities, you will be classified according to salary group 13 (75%) of the TVöD-Bund. In addition, you will receive a special payment (the “Christmas bonus”) equivalent to 60% of one month’s salary. You can find all information about the TVöD-Bund collective agreement on the BMI website.
Organisation/Company: Jülich Research Centre.
Field of research: Engineering » Electrical Engineering; Physics » Mathematical Physics; Physics » Computational Physics
Research profile: Early-stage researcher (R1).
Country: Germany.
Application deadline: 30 March 2026.
More information:Euraxess.
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