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and devices in brain-computer interfaces: Including novel brain-computer interfaces, micro/nano electrodes, large-scale neural information recording, encoding/decoding, and brain-machine interaction
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of brain development and neurodevelopmental disorders. This person will apply and develop computational methods to analyze datasets of varying modalities, such as RNA-seq, ATAC-seq, and spatial
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on their background and interests: investigating the interface of metabolism and brain health and how metabolic alterations impact normal brain function, or contributing to neurodegeneration and cancer-adjacent
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Postdoctoral position for the project Human AI Collaboration: Imaginaries, Interventions, Interfaces
full project description here, including a detailed description of SPs and WPs: https://pure.au.dk/portal/da/projects/human-ai-collaboration-imaginaries-interventions-interfaces . Information about the
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immunotherapies for cancer patients with brain metastasis. Our group works at the interface between immunology and cancer biology combining the use of preclinical models of cancer and human samples with state
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algorithms will subsequently be developed, trained and tested to identify markers of reduced brain resilience during ageing. The project adopts an interdisciplinary approach at the interface of neuroscience
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synergize with our faculty engaged in cellular/molecular, cognitive/behavioral, and systems neuroscience. Other areas of interest include, but are not limited to, brain-computer interfaces, computational
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 6 hours ago
to measure cognitive processes; human-computer interactions; AI-informed brain-computer interfaces; or AI models of attention, language, and memory. The position will build on existing expertise in our
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transcriptomic and circuit-mapping approaches to determine how molecularly defined neural populations control food seeking, consumption, and satiety. More information can be found at https://sternsonlab.com
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interface of human and artificial intelligence from the perspective of neurodevelopment and its disorders. Great technical strides are prying open the black box of the brain, while artificial deep-learning