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to develop novel, bio-inspired neural networks that flexibly and robustly control locomotion in multi-limbed robots. "Self-organised clocks for reliable spiking computation" (Supervisor: Prof Timothy O'Leary
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nonlinear control and optimisation to develop novel, bio-inspired neural networks that flexibly and robustly control locomotion in multi-limbed robots. "Self-organised clocks for reliable spiking computation
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will be defined, decomposed and assessed through attention to artefacts and practices across a range of sectors and disciplines. Focusing on the automotive context, the project will develop a
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of our approach is the innovation of novel methods to investigate genome function. For example, we have recently developed ways to map the binding of nucleic acid-interacting drugs and small molecules
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therapy (Simpson et al. in preparation*). When these local metabolic / immunologic changes happen during pancreatic cancer evolution remains unknown. More importantly, whether these spatial changes can be
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used. AI methods for generating regulatory hypotheses between genes, hormones and physical properties will also be developed. Applicants must have/be close to obtaining a PhD or MPhil in Computational
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target, since all known treatment resistance mechanisms are downstream of, and dependent on FOXA1. However, FOXA1 has been a difficult protein to study for technical reasons. We have developed a novel tool
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Ascl1 are important. We have undertaken a comprehensive discovery experiment to identify all the proteins that can physically interact with Ascl1, using a method we developed called RIME (Rapid
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participants Ideally, practical skills in one of (a) programming, (b) machine learning, and/or (c) design Responsibilities Developing and conducting novel research projects individually and on teams Developing a
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to better understand community perspectives and identify culturally appropriate engagement approaches. Prepare the ethics application and develop participant-facing materials. Contribute to the public