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Field
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energised — not deterred — by problems that sit between physics, learning and the messy real world. Your experience and profile: a PhD (completed or near completion) in Machine Learning, Computer Vision
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(SEM): Electron Back- Scatter Diffraction (EBSD), Electron Channeling Contrast Imaging (ECCI), and other SEM-based modalities Expert on modalities in the transmission electron microscope (TEM
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model and behavior, 2) animal survival and non-survival surgeries 3) confocal/two photon imaging, 4) synaptic biology or physiology. Candidates in ABD (all but degree) status will also be considered
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supervision, this position is responsible for conducting multi-proxy analyses of legacy Antarctic sediment cores housed at the Gulf Coast Repository, including sedimentological, geochemical, and imaging-based
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postdoctoral fellow in the laboratory of Wendy Liu, MD, PhD in the Department of Ophthalmology at Stanford University to conduct collaborative projects in vision research. Position Description: Our laboratory is
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within this field. Your work tasks In this position you will conduct research within Computer Vision and Deep Learning, with a particular focus on the development of an AI-powered framework
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participatory (P4) neurology. The work focuses on the impact of medical and lifestyle risk factors on brain network outcomes. Ongoing projects involve advanced brain imaging, dynamic functional connectivity
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candidate will possess hands-on experience in brain slice or cellular electrophysiology, confocal and super-res imaging of synapse structures, structural biology including cryo-EM and drug discovery workflows
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for image guided radiation therapy. The Fellow will have access to numerous state-of-the-art medical linear accelerators, CT scanners, and a FLASH-capable ProteusONE proton therapy system in the department
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instrumentation. The goal of the project is to design and develop a wearable ultrasonic imager, combined with optical measurements, for monitoring uterus contractions during pregnancy to detect the early signs