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The National Industry PhD Program is an Australian Government initiative to enhance workforce mobility among graduate researchers, and to promote knowledge transfer between academia and industries
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? We invite applications for a PhD position, focusing on the design and implementation of Spiking Neural Networks (SNNs) using CMOS technology. Project Overview This PhD position is part of a
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of neural hydrology, where hydrological models are directly learned from data via machine learning (e.g., LSTM neural networks, [1]). Initially, these models ignored all physical background knowledge and did
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Two fully-funded 3-year PhD studentships are available in Neuromorphic and Bio-inspired computing at the interface between control engineering, electrical engineering, computational neuroscience
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for tomagraphic imaging in tissue Neural network correction of distortions in acoustic transducers web page For further details or alternative project arrangements, please contact: alexis.bishop@monash.edu.
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large-scale neural models of the early visual system. Requirements The successful applicants will have: A solid computational background, an interest in cognitive neuroscience and strong deep learning
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working memory contents held within. Second, we will use computational spiking-neuron models to explain the results of the experiments and implement the neural mechanisms responsible. These models will also
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academic approval, and the candidate will be enrolled in one of the general degree programmes at DTU. For information about our enrolment requirements and the general planning of the PhD study programme
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Qualification Type: PhD Location: Nottingham Funding For: UK Students Funding amount: Full tuition fee waiver pa (Home Students only) and stipend at above UKRI rates pa (currently at £20,780
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format. This will allow combinations of neural networks with physics models. The project brings together PhD students and senior researchers from multiple disciplines to tackle challenges in sustainable