As demand for edge computing grows, there is an increasing need for systems capable of processing data locally with minimal latency and low energy consumption. Traditional computing architectures based on CMOS technology and the von Neumann model struggle to meet these requirements, as the separation of memory and processing units leads to data-transfer bottlenecks and increased power consumption.
PHINDER, short for Picosecond-scale Photonic Heterogeneous Integrated Neuromorphic Detector, is a European research initiative funded by the
EIC Pathfinder 2025 program, bringing together leading academic institutions and innovative companies to address these challenges. The project aims to develop neuromorphic photonic sensor systems capable of analysing light signals from complex processes at the picosecond scale while operating with extremely low energy consumption. The platform combines nanostructured III–V semiconductor nanowires, programmable photonic waveguides, and neuromorphic sensor arrays into a unified hardware system that processes time-varying optical signals directly on-chip.
Coordinated by Luleå University of Technology, the consortium includes Lund University, NanoLund, Eindhoven University of Technology, Universidad de Oviedo, Universidad de Cantabria, Istituto Nazionale di Fisica Nucleare, and Hewlett Packard Enterprise.
The project develops nanowire-based optoelectronic devices integrated with InP photonic circuits to realize photonic spiking neural networks. By combining modelling, fabrication, and hybrid nanowire–waveguide integration, the project aims to enable ultrafast and energy-efficient optical signal processing and demonstrate its potential for advanced sensing and data-processing applications. The modelling work focuses on the design and simulation of the nanowire–photonic interface and the overall photonic neural network architecture. Eindhoven University of Technology will study optical coupling between nanowires and InP waveguides using different approaches to achieve efficient low-loss light transfer. The work also investigates nanophotonic structures to address optical mode mismatches and uses device-level simulations to support system-level network design. The fabrication work aims to develop a planar InP photonic platform capable of integrating nanowire devices with photonic integrated circuits. This includes the development of waveguide-based photonic circuits and coupling structures enabling hybrid nanowire integration. Additional activities involve device integration, electrical contacting, and chip packaging to enable experimental testing. The final phase focuses on the experimental demonstration of photonic spiking neural network architectures. This includes characterization of nanowire optoelectronic devices, evaluation of coupling structures, and testing of reconfigurable photonic circuits implementing neural network connectivity. Experimental validation will assess the performance of the platform for representative signal-processing tasks.
The ideal candidate must have:
- A master’s degree (or an equivalent university degree) in photonics, electro, applied physics or similar.
- A strong background in integrated photonics, preferably on III–V or InP platforms, with hands-on experience in waveguide and coupler design using electromagnetic simulation tools
- Experience with reconfigurable photonic circuits, such as Mach–Zehnder interferometer meshes, and an interest in photonic or neuromorphic computing are highly desirable.
- The candidate should be familiar with cleanroom fabrication processes for photonic integrated circuits and with experimental characterization of photonic devices, including ultrafast or time-resolved optical measurements.
- A systems-oriented mindset is essential, with the ability to translate device-level parameters into circuit- and system-level performance metrics.
- Strong interdisciplinary collaboration skills are required, enabling effective interaction with experts in nanowire devices, neuromorphic algorithms, and system simulation.
- Excellent scientific communication skills and the ability to contribute to an international research consortium are also expected.
- He/she should be fluent in spoken and written English (C1 level).