Rapid advances in artificial intelligence technologies have led to powerful models and algorithms that have revolutionized many applications across all fields of science and technology. Deep learning performed within artificial neural networks has yielded new ways to process data, leading to sophisticated systems with impressive functionality and benefits. However, conventional computing hardware is reaching its limits in terms of energy efficiency and speed. A new approach to computing hardware is needed. Novel brain-inspired or neuromorphic chips working with biologically inspired spiking neural networks have gained attention as they promise highly efficient ways to process data. Important research effort has been dedicated to develop such neuromorphic systems in electronic and photonic hardware.
The PhD positions
Position 1 (Focus: sensing)
This research focuses on the investigation of RTD-based neuromorphic photodetectors capable of producing threshold-based electrical spikes upon receiving low-amplitude optical stimuli. Their integration with other waveguide-based photonic components will be explored as well. This position will aim at proof-of-principle demonstration of spike-based neuromorphic sensing (e.g. event-based sensing).
Position 2 (Focus: sensing)
This research focuses on the investigation of RTD-based neuromorphic lasers capable of producing threshold-based optical spikes upon receiving low-amplitude electrical stimuli. Their integration with other waveguide-based photonic components will be explored as well. This position will aim at proof-of-principle demonstration of spike-based processing in smart sensing concepts.
Position 3 (Focus: processing)
This research focuses on the investigation of micro-disk type lasers with saturable absorbers, capable of producing low-energy spikes when receiving low-energy optical signals. Novel memristive devices for electric and photonic weighting function will be explored and co-integrated with such all-optical laser neurons. The position will aim at proof-of-concept demonstration of ultra-fast optical spike processing.