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research. We study the fundamental molecular, cellular, and physiological processes that underlie normal and abnormal cardiovascular and metabolic function, and drive the translation of this strong basic
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medical image analysis and natural language processing, with applications in cardiology within a global context. You will be responsible for the design and testing of bespoke AI models for cardiac imaging
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environment for the pursuit of cutting-edge cardiovascular and metabolic research. We study the fundamental molecular, cellular, and physiological processes that underlie normal and abnormal cardiovascular and
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Klenerman in the Yusuf Hamied Department of Chemistry, from October 2025 for up to 2 years. This is a collaborative project with Professor Clare Bryant in Clinical medicine and aims to image and characterise
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several benefits, including thermal conductivity, electrical insulating and creating the necessary structural integrity needed around the battery. However, this process can be slow, induces an element of
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focus will be on biomechanics, image processing, machine learning (ML), artificial intelligence (AI), and metrology, the student will also contribute to the co-design of cadaver experiments and data
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scientist to lead the analysis and interpretation of multimodal imaging, including spatial transcriptomics, single cell and large-scale omics data, digital pathology, using cutting-edge AI and machine
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that benefit everyone. The successful candidate will have a good understanding of image processing, multi-modal image registration, and ultrasound imaging. The post involves the development of software for fast
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would be doing: Process and analyse large-scale calcium imaging datasets from multisensory experiments, including neural responses from visual and auditory cortices recorded over multiple days Apply and
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- and time-specific innervation that extends into adolescence. Our lab has used whole-brain tissue clearing, light-sheet imaging, and machine learning to map the spatial and temporal dynamics of serotonin