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Field
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Job Description The Institute of Mechanical and Electrical Engineering at SDU invites applications for a PhD position in Neuromorphic Brain-Computer Interface Design. Are you a multidisciplinary
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looking for a Postdoctoral Research Associate who has: a PhD in a quantitative field (e.g., physics, mathematics, computer science) interest and experience in simulating and analyzing multivariate time
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Background Scholarship code: IND-25122 Expressions of interest - open until filled. This is an industry-linked PhD scholarship. This scholarship is created by La Trobe University in collaboration
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for acquiring data and sharing information related to the research project. PhD in Computer Science or Engineering, Biomedical Engineering, Neuroscience, Bioinformatics, or other relevant field. Experience with
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 15 hours ago
, cell motility and imaging. The Department houses one PhD program: the Cell Biology and Physiology Curriculum in which there are currently enrolled 48 PhD candidates. The Department has approximately 55
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general planning of the PhD study programme, please see DTU's rules for the PhD education . Assessment The assessment of applicants will be made by Assistant Professor Raphael Ferreira together
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feedback control, you will uncover fundamental connections between physical dynamics and neural network representations. We seek a highly motivated PhD candidate with an excellent master’s degree in physics
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are recruiting three PhD students with distinct research foci: PHD 1: The functional role of neural rhuthms for inter-area brain network communicartion PHD2: The neural code for multi-item representation in
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doctoral degree PhD, MD, or MD/PhD in neuroscience, neurobiology, physics, psychology, computer science, electrical engineering, neuroengineering or related discipline, and a track record of federally funded
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The successful applicant will have (or be near to completion of) a PhD in Computer Science with expertise indeep neural networks, preferably with expertise in any of the following subfields: signal processing and