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developed goal-sequence generalization task. The project will integrate high-density silicon probe recordings, optogenetics, pharmacology and advanced computational tools to analyse neural algorithms
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distribution of immune cells using analyses such as immunohistochemistry or immunofluorescence. You will have expertise in developing multi-parameter (>4 colour) immunofluorescence approaches, experience in
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consists of three major parts: sensor printing, circuit design and integration and developing of an AI algorithm and using it to teach the sensor to selectively measure desired gases . In this role, you will
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novel sensing approaches to combine with machine learning algorithms to solve real-world problems in food manufacturing. You will have sound knowledge in electronic engineering, embedded systems design
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that influence global ocean mixing, heat and nutrient distribution, and climate dynamics. Despite their importance, these currents remain poorly understood due to their intermediate scale and intermittent nature
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extracellular vesicles with **GENE**-mRNA; • In vivo delivery of first vector and evaluation of expression/distribution; • In vivo delivery of first vector in acute MI and evaluation
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to reconstruct the tree-of-life on Earth, it allows us to reveal how biological function has evolved and is distributed on this tree, and it is the foundation that enables us to use model organisms
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is developing cutting-edge research on all aspects of computational imaging, from theory and algorithms, to applications in astronomy and medicine. Dr Wiaux is a Professor in the School of Engineering
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the use of Fibre-Optic Distributed Temperature Sensing and geophysical borehole logging. Show proven experience in numerical heat & transport modelling. To be successful at shortlisting stage, please ensure
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type (iv) work with the computational biology team to transfer this information into a AI algorithm that can distinguish neurodegenerative and neuroprotective phenotypes (v) work with colleagues in