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for generative or analytical purposes (e.g., generative adversarial networks, convolutional neural networks, diffusion models, or other emerging methods), with evidence of application in research or professional
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learning architectures including generative models, particularly for sequence or structural data (e.g. transformers, graph neural networks) Proved experience in working independently and as part of a
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for sequence or structural data (e.g. transformers, graph neural networks) Proved experience in working independently and as part of a multidisciplinary team Evidence of strong communication and scientific
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modelling of the C. elegans neural network. The lab also uses Two Electrode Voltage Clamp (TEVC) electrophysiology and molecular biology techniques to characterise receptors. There are a broad range of
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researcher to investigate the neural mechanisms underlying decision-making, using the fruit fly Drosophila melanogaster as a model system. Funded by the BBSRC, this project will combine innovative behavioural
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of biological brains. Spiking neural networks (SNNs) can offer increased processing speed and reduced power consumption, especially when implemented on dedicated hardware (neuromorphic chips or FPGAs). Standard
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graph neural networks for complex sensor networks such as those involved in brain imaging Develop and test data-driven methods for image and video processing for microendoscopy. Key Duties and
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project is to develop a series of surrogate models focusing notably on Physics-Informed Neural Networks to emulate the process of sediment deposition, diagenesis, and potentially fracturing, working closely
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approximation theory can be automated by a (neural network) guided search over the action space of standard tools (e.g., Hölder inequalities, Sobolev embeddings, ...). Certain proofs in these fields require
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project funded by the Waterloo Foundation , exploring the neural mechanisms of balance control in children with and without Developmental Coordination Disorder (DCD). This is a hands-on role that will