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Field
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, neural networks, and statistical modeling toolboxes (such as pytorch, stan, network methods) . In addition to state of the art computational infrastructure, we have access to exciting non-public data
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network activity, Neuroscience research, Human cortical organoids, Synaptic plasticity, Brain organoids, Neural plasticity, Human neural networks, Neurobiology, Electrophysiology Financial Support This
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to compare deep neural network and other artificial representations to each other. By applying the new techniques to state-of-the-art architectures, you will test our new methods against existing ones and
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expectations? By using computational models (including probabilistic models and neural language models), we will be able to answer these types of questions. In addition, our project will benefit computational
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simply by paying attention to what they “hear”? Or do they need to come prepared with certain expectations? By using computational models (including probabilistic models and neural language models), we
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and prosthetic devices in the real-world. This PhD project offers the opportunity to work on pioneering research that combines state of the art computational modelling (deep neural networks) and
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. Work on this project will require research into novel methods that extract information from text that can be combined with the acoustic training data to inform flexible neural network structures and
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vision, machine learning, deep learning and neural networks, as well as courses in python, GPU programming, mathematical modeling and statistics, or equivalent. We are looking for candidates with: A solid
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to neural pathways. Biomarkers identified will then be used to cross reference to human databases to test for translational relevance in humans. You will train within a leading interdisciplinary team across
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the past ten years thanks to artificial intelligence, mainly in the form of deep convolutional neural networks. In parallel, functional analysis of tissue samples via novel microscopy techniques and spatial