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Field
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spared from injury into personalized musculoskeletal models to enable robust neural control of robotic assistance in stroke survivors. Real-time characterization of the effect that electrical stimulation
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currently exploring a range of exciting topics at the intersection between computational neuroscience and probabilistic machine learning, in particular, to derive mechanistic insights from neural data. We
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currently exploring a range of exciting topics at the intersection between computational neuroscience and probabilistic machine learning, in particular, to derive mechanistic insights from neural data. We
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neural network models, produce stimuli for artificial and biological agents, participate in experiments with chicks maintained in the Biological Services Unit, contribute to lab meetings and research
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and group affiliations, both behaviourally and neurally. Your job responsibilities As Postdoc in Neuroscience your position is primarily research-based assignments. You will contribute
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well as in designing coordination strategies for them. Our recent work on RL and graph neural networks (GNNs) demonstrate some of our key research directions relevant for this position. A high degree of self
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techniques including deep neural networks and large language models (such as GPTs), with state-of-the-art functional genomics approaches, including crop genomics, genome editing, and single cell multiomics
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work on a study funded by the National Institute of Mental Health. The major goal of the project is to use a combination of modern circuit neuroscience technologies to establish neural circuits
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contributes advanced tools for spatial molecular phenotyping, including smFISH-based spatial transcriptomics, spatial validation of single-cell data, and gene regulatory network mapping during neural
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fundamental mechanisms of neuronal loss to better understand why neurons die or axons are damaged to ultimately establish new strategies for the preservation or restoration of neural tissue. We use multiple