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Field
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of short-axis MR image sequences. Training You will be based at the Vision Computing Lab within the School of Computing Sciences, which specializes in deep learning for medical image analysis and neural
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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 routines and
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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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We are looking for an enthusiastic image analyst with suitable technical expertise to support an exciting research programme focused on the development and validation of novel technologies
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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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benefit from the extensive and broad expertise in AI and biomedical computing at the School of Biomedical Engineering & Imaging Sciences. The work will be done in close collaboration with a
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(computer vision technologies). The interdisciplinary nature of this PhD will require the integration of environmental science, engineering, and community science methodologies. Supervisors: Primary
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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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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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quality, diversity, and biological relevance using standard metrics and expert review. Anonymised digital images from tissues in biobanks will be used to train generative models on university computing