MSCA PF with host support from the UK Multidisciplinary Centre for Neuromorphic Computing

You’ll have the opportunity to collaborate with world-leading experts across our consortium of partner institutions:

Aston University

(Focus: Human Neurobiology, Organoid-Device Integration, Hybrid Systems, Photonic SNNs applied)

• Neuronal network activity and plasticity in human cortical organoids

• Inference, entropy and cross-communication in human cortical organoid arrays

• Neuromorphic device designs inspired by human cortical organoid dynamics

• Hybrid silicon-cortical neuromorphic systems

• Photonic spiking neural networks

• Photonic extreme learning machines

Loughborough University

(Focus: Human Neurobiology, Organoid Structures and Modelling, Stimulation Protocols)

• Evolving Structures and Connectivity in Human Cortical Organoids

• Development of Computational Models of Synaptic Behaviour in Organoids

• Cortical Organoid Networks

• Microfabrication of Neural Networks

• 4D Bioprinting Methods for Organoid Modelling

Southampton University

(Focus: Foundational Materials, Energy-Efficient Devices, Optoelectronic Synapses, Sustainable Manufacturing)

• Ultra-Low-Power Optoelectronic Synapses using 2D Materials

• Nanopatterning and Integration of Novel Materials for Neuromorphic Devices

• Hybrid Operational Modes for Energy-Efficient Synaptic Devices

• Integrating Neuromorphic Devices with Sustainable Photonic Sources

• Reconfigurable Photodiode Arrays for In-Memory Neuromorphic Sensing

Queen Mary University of London

(Focus: Foundational Materials, PCMs, Perovskites, Photonic Architectures, ML for Materials/Architectures, EM Modelling)

• Machine Learning and Novel Phase-Change Materials for Optical Memories

• Perovskite-Based Neuromorphic Components for Photonic Systems

• Perovskite Components for Industrial Neuromorphic Systems

• Computations based on Photonic Neuromorphic Computing

• AI-Driven Material Discovery for Scalable Photonic Neuromorphic Architectures

Cambridge University

(Focus: photonics-based analogue computing and computing architectures for AI; Hybrid quantum–classical algorithms and scaling laws for optical AI accelerators)

• Photonics-based analogue computing and computing architectures for AI

• Quantum Effects for Neuromorphic Systems

• Hybrid Quantum-Classical Computing Architectures for AI

• Gain-Based Photonic Systems for Complex AI Problems

Oxford University

(Focus: Hybrid Quantum-Classical Computing, Energy-Efficient Weight Updates, Reliable Photonic Devices, Integrated Hardware, MAC Operations)

• Energy-Efficient Weight Update Mechanisms for Neuromorphic Hardware

• Photonic Neuromorphic Devices

• High-Density Integrated Neuromorphic Hardware

• Photonic Device Development for Energy-Efficient MAC Operations

University of Strathclyde

(Focus: Photonic SNNs, Scaling Architectures, Reservoir Computing, Event-Based Sensing)

• Neuromorphic photonic integrated technologies.

• Photonic Spiking Neural Networks

• Real-Time Data Analysis and Pattern Recognition using Spiking Neural Networks

• Photonic Reservoir Computing Systems for Spatiotemporal Data

• Integration of Light-Enabled Event-Based Sensing with Photonic Neuromorphic Systems