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Field
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significant mathematical and computational background to learn and develop new AI methods. While demonstrated experience in computer vision and deep learning for pathology or other biomedical image analysis is
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) for protein analysis and interaction studies Microscopy techniques, including fluorescence microscopy, confocal microscopy, and immunofluorescence imaging Chromatin immunoprecipitation (ChIP) assays to assess
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; significant practical experience in 3D image analysis or computer vision; knowledge and experience in scientific programming (python (preferred), Matlab or other relevant language) with application to image
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solutions informed by the latest ideas in medical imaging AI, computer vision and robotic guidance; and evaluate models in simulated and real clinical scenarios. Evaluation may involve quantitative studies
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, with a focus on building multimodal AI models to predict dental caries progression. The successful candidate will work on developing deep learning and computer vision models using longitudinal dental
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healthcare, dental, vision, pension plans, competitive pay, generous paid time off, tuition assistance, life insurance and long-term disability insurance. As an Equal Opportunity / Affirmative Action employer
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utilises cutting-edge recording techniques, including two-photon calcium imaging, high-density Neuropixels electrophysiology, and spatial transcriptomics, alongside computational analyses, to uncover novel
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/field personnel in research. Initial studies will focus on burn wounds, improving healing and assessing multiple wound factors using imaging and sensors. What you need to know Salary: Compensation will be
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Responsibilities Specific responsibilities will include data acquisition (flow visualization, particle image velocimetry (PIV), pressure, acoustic, and high-speed video/kinematic measurements), analysis, and
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figures for publications and grants. Calcium imaging: Utilizing calcium dyes or genetically encoded calcium sensors (i.e. GCaMP) to measure and quantify intracellular calcium levels in a live brain slice