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We have 78 neural networks PhD Projects, Programmes & Scholarships



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neural networks PhD Projects, Programmes & Scholarships

We have 78 neural networks PhD Projects, Programmes & Scholarships

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Next-Generation Spiking Neural Networks Architectures and Machine Learning Algorithms

Spiking Neural Networks (SNNs) represent the so called ‘third generation’ of artificial neural network models, that bridge the gap between neuroscience and artificial intelligence by relying on biologically realistic models of neurons and network architectures to carry out computations. Read more

Autonomous Drone Surveys and Convolutional Neural Networks for Bridge Maintenance: A Predictive Approach Using Finite Element Analysis

Objective. The primary objective of this research is to develop a comprehensive framework for bridge maintenance that integrates autonomous drone surveys, convolutional neural networks (CNNs), and Finite Element analysis. Read more

Building connections between model predictive control and neural networks

Feedback control enables dynamical systems to interact autonomously and safely with the real-world. The classical approach to feedback control system design involves first identifying a model of the system and then solving an optimal control problem to generate a control policy. Read more

Neural Networks for Complex Dynamical Systems

Details. Dynamical systems are often solved/integrated by a suitable numerical discretisation method in such a way that certain properties of the underlying systems will be preserved. Read more

PhD Scholarship in spiking architectures for event-based computing

The recent advances in spiking neural networks (SNNs), standing as the next generation of artificial neural networks have demonstrated clear computational benefits over traditional frame/image-based neural networks. Read more
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Large-scale photonic-electronic integration for next generation neuromorphic computing systems

Start date. October 2023. Duration. 3.5yrs. Description. Neuromorphic computing has gained huge momentum in the last decade thanks to the emergence of novel machine learning algorithms such as deep learning. Read more

Neuromorphic RF sensing and processing

Artificial Neural Networks (ANN) have been a research topic since 1940's, even though it is only after the formalisation of the backpropagation algorithm for ANNs in 1986, that it has become possible to effectively train a non-linear ANN with multiple hidden layers of neurons. Read more

Effects of insecticides on brain activity

Project Overview. Overview . This project is an exciting new collaboration between the University of Reading and Syngenta Group, to investigate the mammalian toxicity of insecticides and understand their effects on the brain. Read more

Develop a machine learning approach to multimodal imaging

The emergence of antimicrobial resistance (AMR) threatens to undo the advances of modern medicine, making commonplace interventions like major surgery or cancer chemotherapy effectively impossible. Read more

Learning a universal biomolecular force field

Molecular dynamics has been successful in obtaining biological insights by simulating the motion of biomolecules. Increases in compute power mean that simulations will soon reach the time scales on which much of biology happens. Read more

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