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vision and machine learning methods for multimodal imaging and real-time analysis in colorectal cancer screening and treatment. They will contribute to the design of AI algorithms for polyp detection
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qualified in relevant subject area (or nearing completion) Good knowledge of computer vision algorithms for image and video processing Strong experience in machine learning or deep learning for medical image
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neurosurgical centre. In this role the successful candidate will develop deep learning algorithms and validate models on diverse clinical data which include magnetic resonance imaging (MRI) and computed
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sitting within a leading programme of clinical, health and bioinformatics at the South London and Maudsley (SLaM) Biomedical Research Centre (BRC) and forms a key component of both the Centre
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sitting within a leading programme of clinical, health and bioinformatics at the South London and Maudsley (SLaM) Biomedical Research Centre (BRC) and forms a key component of both the Centre
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scientists. Based across King’s Denmark Hill, Guy’s, St Thomas’ and Waterloo campuses, our academic programme of teaching, research and clinical practice is embedded across five Departments. The Department
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scientists. Based across King’s Denmark Hill, Guy’s, St Thomas’ and Waterloo campuses, our academic programme of teaching, research and clinical practice is embedded across five Departments. About the role
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82304 for the Epilepsy Navigation (EpiNav™) Software Platform. EpiNav™ provides state-of-the-art computer-assisted support for the planning of stereotactic neurosurgery procedures. It has been in daily
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units that are funded by the Horizon Europe Programme. The consortium team will develop an advanced Multi-Processor System on Chip prototype in FD-SOI 28nm CMOS technology that tightly integrates
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About us: The Faculty of Natural, Mathematical & Engineering Sciences (NMES) comprises Chemistry, Engineering, Informatics, Mathematics, and Physics – all departments highly rated in research