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, including functional Magnetic Resonance Imaging (fMRI), functional Ultrasound Imaging (fUSi), and computational modelling of emotion-related behaviours. This is a full-time, fixed-term position starting
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to accelerate the design and discovery of novel materials. The Materials Theory Group has a background in using first principles methods to examine electronic and thermal transport, magnetic properties
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of coronal jets and/or analysing PSP data to understand how magnetic switchbacks form and evolve within the solar wind. Key responsibilities: To conduct individual and collaborative research projects under
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, cryogenic instrumentation, high magnetic fields, 2D material sample preparation, and x-ray scattering. Good written and oral communication skills are required, as demonstrated through scientific publications
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 8 hours ago
Experience * Proficiency in analyzing functional magnetic resonance imaging data. * Demonstrated skill in manuscript preparation, managing large datasets, multivariate analytical approaches, and/or
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magnetospheres. The goal is to better understand the plasma dynamics, the launching of relativistic magnetized outflows, and particle acceleration in the close environment of compact objects. The candidate will
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of Biomedical Engineering at the University of Delaware under the supervision of Professor Curtis Johnson and focuses on brain magnetic resonance elastography (MRE) research supported by funding from the National
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nationally ranked, research-intensive unit with over $25 million dollars of research-grade instrumentation including spectrometers (nuclear magnetic resonance, mass, optical, x-ray), chromatographs (gas and
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spectroscopy (EIS), solid-state nuclear magnetic resonance (NMR), and X-ray/Neutron scattering techniques. We are particularly interested in candidates with prior experience in preferably all of the following
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data (PET, CT, Magnetic Resonance Imaging with Late Gadolinium Enhancement – MRI-LGE) and clinical variables. The approach encompasses unsupervised multimodal registration, three-dimensional deep