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will be assessed at each stage of the recruitment process. * Please note that this is a PhD level role but candidates who have submitted their thesis and are awaiting award of their PhDs will be
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potential applications in audio and music processing. Standard neural network training practices largely follow an open-loop paradigm, where the evolving state of the model typically does not influence
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on autofluorescence (AF) imaging and Raman spectroscopy for detection of metastatic lymph nodes during breast cancer surgery. Engaging with and reporting to Dr Alexey A. Koloydenko (Department of
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cell biology; cancer; cardiovascular; nutrition and diabetes; genetics; infection and immunology; imaging and biomedical engineering; transplantation immunology; pharmaceutical science; physiology and
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diabetes; genetics; infection and immunology; imaging and biomedical engineering; transplantation immunology; pharmaceutical science; physiology and women's health. We also have thriving research programmes
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Population and Data Science. The Institute was ranked the number one place in the world to study ophthalmology (CWUR 2017 world rankings), attracting principal investigators, post-doctoral fellows and PhD
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cell biology; cancer; cardiovascular; nutrition and diabetes; genetics; infection and immunology; imaging and biomedical engineering; transplantation immunology; pharmaceutical science; physiology and
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for conditions such as otosclerosis. The position requires expertise in medical image analysis, proficiency with neural network architectures (particularly CNNs for segmentation tasks), and experience processing
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programme investigating early lung fibrosis at King’s College London. It is anticipated candidates will have a relevant PhD in immunology or respiratory sciences, and have experience with cell culture
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fluorescence-lifetime detection (Fast-FLIM) and temporal focusing. This instrument will deliver quantitative, sub-second imaging of live three-dimensional cell-culture and organoid models, advancing fundamental