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model of the non-transparent structure. Using this approach, we aim to build a microscope that can look inside very complex materials without loss of image quality. Your role is to build flexible 3-D ray
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to fluorescently labelled AP-L complexes and analyze how the cells accumulate and spread the complexes over time using live cell imaging, immunocytochemistry, ELISA, Western blot, electron microscopy and other
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Provide human experts with a reliable second opinion This project integrates image processing, data analytics, machine learning, and computational modelling, with applications in aerospace, mechanical
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required staff training, process redesign and collaboration among diverse experts to adapt systems and practices. Consequently, new tools and methods were developed to support organisations (Bhalavat et al
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The Computer Vision Group is looking for an aspiring PhD to investigate multi-agentic AI, LLMs, and VLMs applied to agricultural sciences. Currently, established AI models often fail to generalize
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applications in aerospace, rail, automotive and battery technologies. However, current PFA systems suffer from brittleness, moisture‑related defects and narrow processing windows, limiting their wider adoption
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Conventional x-ray imaging is firmly established as an invaluable tool in medicine, security, research and manufacturing. However, conventional methods extract only a fraction of the sample
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persistence in chronic infections (Salmonella, Pseudomonas, and Achromobacter) by integrating spatial modelling, single-cell transcriptomics, advanced imaging data, and machine learning approaches. The goal is
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data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular structures and cellular processes to human health and global ecosystems
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-driven life science framework. Data-driven life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular