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imaging features to phenometabolic signatures from tissue samples taken during surgery and matched to the imaging. The project is part of the imaging theme for the new Nottingham Brain Tumour Research
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to phenometabolic signatures from tissue samples taken during surgery and matched to the imaging. The project is part of the imaging theme for the new Nottingham Brain Tumour Research Centre of Excellence. This is a
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and imaging diagnostics. The degree of resolution – already at single-cell level – will continue to increase in all disciplines of life sciences, and the need to process and combine huge data sets
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University. This doctoral project is funded by the ANR project Hotspot 2025, which is a collaborative project between two research teams working in biomedical photoacoustic imaging (Team: Medicine and
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science/biomedical engineering or of relevant scientific field A solid background in machine learning Extensive experience with either computer vision or image analysis Good knowledge of deep learning
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application! We are looking for a PhD student in biomedical engineering with a focus on deep learning for medical images Your work assignments The position focuses on developing methods for federated learning
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/biomedical engineering or of relevant scientific field A solid background in machine learning Extensive experience with either computer vision or image analysis Good knowledge of deep learning packages
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imaging. Your Profile: The successful applicant must have the following: • Master’s degree in physics, biophysics, biomedical engineering, computer engineering or electrical engineering. • Excellent track
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engages in research, education and services aligning with CING’s mission to advance biomedical research. The successful candidate will join for a 36-month full-time PhD contract and will carry out research
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and experience. Job responsibilities include: • Develop or identify quantitative tools for imaging data processing, including diffusion, anatomic, and BOLD fMRI. • Oversee data quality assurance/quality