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The Department of Electrical and Computer Engineering at the University of Virginia is accepting applications for research scientist position for machine learning methods for magnetic resonance
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) and have a background in imaging, image analyses, machine learning, and software engineering. References: (1) A. J. Brooks et al, “Neutron interferometry detection of early crack formation caused by
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or equivalent required. Graduate of accredited Radiologic Technology /Diagnostic Imaging Program ARRT registered. State of Florida License as a General Radiographer Basic Life Support (BLS) certificate required
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of dislocation stress fields (in collaboration with CEA Saclay). - Program the diffraction procedures to generate images comparable to Electron Channeling Contrast Imaging (ECCI) obtained using a Scanning Electron
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Radiology, Neuroradiology, Interventional Radiology, Nuclear Medicine, Intelligent Imaging Informatics (I3), Research, and Physics. The Body Radiology section focuses primarily on pediatric cancer imaging and
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the Faculty of Engineering, and it offers a full spectrum of BME programmes, from BSc, MSc to PhD. The team is the first group to offer Biomedical Engineering related undergraduate programme in Hong Kong, and
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the consortium Your Profile: Excellent Master and subsequent PhD in computer science, engineering, biophysics, applied mathematics, computational biology or a related field Proven programming expertise in Python
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imaging of subfield scattering targets." Optics Letters 41(21): 4959-4962, 2016. http://dx.doi.org/10.1364/OL.41.004959 Barnes BM, et al: "Three-dimensional deep sub-wavelength defect detection using l=193
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9 Feb 2026 Job Information Organisation/Company Grenoble INP - Institute of Engineering Department Engineering Research Field Engineering Researcher Profile First Stage Researcher (R1) Positions
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application! We are looking for a PhD student in biomedical engineering with a focus on deep learning for medical images Your work assignments The position focuses on developing methods for federated learning