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Field
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postdoctoral fellowship at ENS Lyon in the field of machine learning. The position is part of the research project "Neural networks for homomorphic encryption", funded by Inria. Fully homomorphic encryption (FHE
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effects for drug discovery. The successful candidate will play a leading role in developing gene perturbation models that combine foundation models (FMs) and graph neural networks (GNNs) to accelerate
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, doctoral students and undergraduates around a common goal: to understand the neurophysiological mechanisms and brain networks involved in neurological and psychiatric disorders (epilepsy, Parkinson's disease
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Neural Injury Group and the Neuromusculoskeletal Health and Science Lab with responsibility for contributing to a multi-lab MRC-funded research project aiming to develop advance humanised pain models
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analysing Cortically-Embedded Recurrent Neural Networks (CERNNs) that simulate large-scale neural dynamics during cognitive tasks. These models integrate species-specific neuroanatomical constraints to enable
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epilepsies. They use a range of advanced genomic techniques including single-cell and spatial multiomic evaluation of epilepsy surgical tissue as well as iPSC-derived neural cultures and mouse models
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contribute primarily to developing and analysing Cortically-Embedded Recurrent Neural Networks (CERNNs) that simulate large-scale neural dynamics during cognitive tasks. These models integrate species-specific
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research on memory and behavior is how the brain responds to environmental stimuli, and a major challenge here is the heterogeneity of cell-signaling pathways, brain cells and neural networks. We study
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force fields (MLFFs) that combine state-of-the-art equivariant neural network architectures with robust, well-calibrated uncertainty estimates. These models will enable fully automated active learning in
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fundamental questions about the transcriptional regulation of inhibitory neuronal development and function in neural circuits, the role of cerebellar circuit dysfunction, and disrupted gene regulatory networks