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underestimated cloud cover response to aerosol perturbation, pointing a key direction for improving climate projections. You will work closely with a Scientist at ETH Zurich to apply a new Neural Network-Based
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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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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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Reporting to Profs Annina Schmid and David Bennett. The post holder is a member of the Neural Injury Group and the Neuromusculoskeletal Health and Science Lab with responsibility for contributing
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The Leibniz Institute for Neurobiology (LIN) is an internationally recognized neuroscience research institute dedicated to understanding the neural mechanisms of learning and memory across
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learning methods. Develop deep learning architectures (e.g., variational autoencoders, graph neural networks, transformers) for cross-omics data representation and feature extraction. Apply multi-view
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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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, 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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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