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The brain is a complex system and monitoring and imaging methods to observe critical neurophysiological variables underlying brain function are limited. This project works at the intersection
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the area of end-to-end modular autonomous driving using computer vison and deep learning methods. This includes developing an efficient and interpretable image processing, vision-based perception and
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Fellow. This role offers the chance to be at the forefront of innovation in chemical biology, with a focus on developing cutting-edge tools for molecular sensing and imaging. Under the guidance of Dr
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experience in at least one of the following would be highly regarded: (i) the theory and simulation of scattering, diffraction and imaging with high energy electrons or X-rays; (ii) solving inverse scattering
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prototype integration to translate sensor outputs into clinically relevant protein biomarker data. The role will involve laboratory-based experimentation, data analysis, and active contribution to scholarly
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PhD student(s) will join a vibrant team of postdocs, academics, and up to four PhD students working collaboratively across modelling, qualitative fieldwork, and optimisation techniques. PhD Research
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imaging, based on absorption, provides good image contrast between high- and low-density materials, such as bones and soft tissue. However, it cannot distinguish subtle density differences between soft
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, augmented virtual reality, voice assistance, and medical diagnosis. This new paradigm is further accelerated by AI chips and ASICs embedded on mobile devices, e.g., Apple’s Bionic neural engine. Compared
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the structure present in food systems dictates functional aspects such as digestion and release of nutrients. Working alongside other postdocs and students focused more on biological aspects of these processes
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, in various formats including images, texts and numeric values. The study of these unstructured data in the pathology laboratory information system (LIS), together with the information from