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thematic research areas, including Biomedical Imaging, Sensing, AI and Wearable Technology, Brain-Machine Interface and Neural Engineering, Molecular/Cellular Engineering and Biomaterials, Precision
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October 2029. Job description The post doc position focuses on research questions related to data integration and visualisation (e.g. digital twins) at the interface between agricultural and biological
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laboratory integrates, under one roof: Chemical synthesis and drug formulation laboratories High-field 7 Tesla MRI Two-photon and confocal microscopy State-of-the-art electrophysiology Brain-machine interfaces
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as PhD candidate in the field of machine learning for materials science. Your immediate leader will be the Head of Department. About the project Can AI interpret graphs like a human materials scientist
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Technician to join our team. Our research focuses on the interface of glial biology and brain cancer, with a particular emphasis on malignant glioma - the most aggressive and lethal form of primary brain tumor
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of cryptographic implementations and hardware-security countermeasures. Experience with hardware reverse engineering, debugging interfaces, or firmware analysis. Experience with machine learning, deep learning
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7 Tesla MRI Two-photon and confocal microscopy State-of-the-art electrophysiology Brain-machine interfaces Mechanical and electronic prototyping workshops Access to advanced microfabrication
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Dr Rebecca Dikow - Director of Research Innovation, Yale University Libraries Dr Gary Motz - Head of Computer Systems, Yale Peabody Museum Jeff Campbell – Associate Director for Cultural Heritage
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-computer interfaces, audio signals for keyword spotting and artificial cochleas, and tactile signals for robot perception. Various types of bio-inspired mechanisms have been investigated in recent years
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BME education, innovative research, and technology transfer. Currently BME has six thematic research areas, including Biomedical Imaging, Sensing, AI and Wearable Technology, Brain-Machine Interface and