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the supervision of Prof Amedeo Chiribiri within the Department of Cardiovascular Imaging, School of Biomedical Engineering & Imaging Sciences, King’s College London. About The Role Applicants should be medically
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under real-world conditions to verify system operation against targets and demonstrate the reliability of the technology for use in backup power, grid stabilisation, and renewable energy integration
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-quality teaching. The Hub for Applied Bioinformatics (HAB) is the Faculty’s focal point for computational biology, delivering bespoke bioinformatics support and training across genomics, transcriptomics
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, alignment, and characterisation of laser-based instrumentation. • Strong experience with computer programming, both for signal processing and experimental hardware control (e.g., C, C++, Python, MATLAB
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-quality teaching. The Hub for Applied Bioinformatics (HAB) is the Faculty’s focal point for computational biology, delivering bespoke bioinformatics support and training across genomics, transcriptomics
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or bioinformatics and a keen interest in cancer biology. Extensive and demonstrated experience in scRNA-seq, spatial transcriptomics, with image analysis experience an advantage. A proven publication
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institutions, and leading industry partners. The successful candidate will contribute to the delivery of high-impact research projects involving AI algorithm evaluation and image data analysis. You will play a
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the supervision of Prof Amedeo Chiribiri within the Department of Cardiovascular Imaging, School of Biomedical Engineering & Imaging Sciences, King’s College London. About The Role Applicants should be medically
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inversion of gravity gradient data, contribute to the development of data interfaces for multi-modal sensor integration, and perform advanced data processing and inference to support subsurface imaging and
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a PhD in Computational Biology, Applied Mathematics, Statistics, Biostatistics, Epidemiology, Bioinformatics, Computer Science, Neurological Genetics or a closely related discipline. Excellent oral