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, MONAI) Strong interest in image analysis / computer vision and pattern recognition, including but not limited to biomedical applications Strong interest in applied machine learning, including but not
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First-class or 2:1 MEng or and MSc with merit (over 60%) in a relevant area i.e. Chemical Engineering, Process Engineering, Chemistry, Materials Science, Geoscience etc. Candidates for socio-politico
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to the subject area. The candidate’s doctoral degree should be primarily focused on computed tomography, image analysis or similar. Essential criteria are: Demonstrated experience in programming (e.g., Python, MATLAB
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3D multiplexed tissue imaging. BAIR supports users at every stage of the imaging process, from experimental design and sample preparation via in-depth training to developing complex automated imaging
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microstructure), and computer science (machine learning and artificial intelligence) to achieve a breakthrough in predictive microstructure imaging with MRI. Within the ADAMI project, you will develop and optimize
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marine sciences, biological oceanography, ecology, or computer sciences. Strong analytical, numerical and practical skills are essential. Experience in coding or applying quantitative methods in a
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$29.95-39.10/hour Type of Position Staff Position Time Status Full-Time Required Education AA Click here for more information about equivalencies: https://hr.uky.edu/employment/working-uk/equivalencies
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departments: Cardiovascular Imaging, Cancer Imaging, Early Life Imaging, Imaging Chemistry & Biology, Biomedical Computing, Surgical & Interventional Engineering, Imaging Physics & Engineering and Digital Twins
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University of California, San Francisco | San Francisco, California | United States | about 12 hours ago
/index.html Department Description The UCSF Department of Radiology Imaging IT team architects, implements, and manages the computer systems and networks needed to support more than 700,000 imaging studies
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oriented to improve digital skills. Access to CSIC infrastructure (e.g., HPC, Bioinformatic and Computational Biology Connection) Where to apply Website https://docs.google.com/forms/d/e/1FAIpQLSeGVtNv_