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Field
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of developing cutting-edge deep learning models for real-time image and video analysis (e.g., segmentation, object tracking, reinforcement learning), with applications to medical imaging and robotic systems. In
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will receive full consideration. Key Responsibilities AI-ready data and analysis for the ePIC Barrel Imaging Calorimeter and our Jefferson Lab program Support for the PRad-II and X17 experiments
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records and medical images, for applications pertaining to patient diagnostics and prognostics. We are seeking a Postdoctoral Researcher to join the team and make significant contributions to the field
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classification, segmentation and regression using combinations of high-resolution LiDAR point cloud data and image data and may draw upon aspects of synthetic data-based learning and domain adaptation. To learn
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About us: We are seeking experts in medical image deep learning to join our team and help develop novel computationally efficient segmentation algorithms. We welcome application from individual with
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) Categories: Senior Research Staff & Post-doctoral Fellow Post-doctoral Fellow/ Senior Research Assistant in the Division of Restorative Dental Sciences, The Faculty of Dentistry (Ref.: 533267) We now invite
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) Extrapolation of photospheric magnetic fields to the corona using various approaches. 2) Quantitative analysis of HXR (imaging spectroscopy from STIX and HXI) and EUV (fluxes and DEMs) sources. 3) Analysis and
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Job Description Apply now Job Title: Postdoctoral Associate Division: Neuroscience Work Arrangement: Onsite only Location: Houston, TX Salary Range: Hiring upto $63,200 FLSA Status: Exempt Work
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Translating deep learning models into clinical settings Experience developing deep learning models for real-time image/video segmentation, object tracking, 3D reconstruction, super-resolution. Have a passion on
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experience in the experimental techniques used in the lab such as optical tweezers and quantitative imaging is advantageous but not required. The terms of employment are very competitive and include housing