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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 4 hours ago
for uterine fibroids using multimodal imaging and clinical information. The postdoctoral researcher will join a multidisciplinary research team consisting of computer scientists, neuroscientists, medical
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). • Advanced quantitative analyses (machine learning, computer vision, multilevel statistics). • Creation and use of Python code for advanced analyses. • Management and monitoring of complex transgenic lines
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We are seeking a highly motivated and skilled individual to join our neuroimaging laboratory, which specializes in multimodal image fusion, multiparametric modeling, and machine learning techniques
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related discipline. Strong expertise in medical imaging and/or machine learning. Excellent programming and research skills. Interest in translational research and interdisciplinary collaboration with
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machine learning. Essential Duties and Responsibilities: Design and conduct experimental studies using structured, correlated, or quantum light to probe samples with reduced dose. Carry out X-ray imaging
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machine learning methods. The successful candidate will lead an independent research project dedicated to identifying abnormal behavior and neuronal activities in circuits of murine models of 22q11.2 and
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scientists. The emphasis will be on enabling high-fidelity image reconstructions from sparse and noisy data, leveraging state-of-the-art methods in compressed sensing, optimization, and machine learning
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 1 month ago
researcher with a background in machine learning and/or biomedical image processing. The ACM Lab is developing software to support AI-driven techniques to rapidly diagnose, track, and treat neurodisorders
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inverse modeling methods, machine learning, and artificial intelligence techniques. Appointment Details: Start date: As early as February 1, 2026. Annual Salary: $52,000 Application review: Ongoing until
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innovative methods for processing and analyzing 7Tesla MRI images of different modalities and formats (NIFTI, DICOM, etc.) using machine learning and artificial intelligence techniques. These methods will be