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, whilst having experience with implementing Bayesian algorithms will be an advantage. A background in biology is NOT required. The post is for up to 6 months, to 31st March 2026. Additional funding is
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research programme in probabilistic AI. The hub will develop the next generation of mathematically principled, scalable and uncertainty-aware AI algorithms. This will be achieved through: bringing together
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reduction (MAR) algorithms, AI-based segmentation, and automated 3D anatomical modelling, promise clearer, more reliable imaging. Integrated effectively into clinical workflows, these advances have the
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. The project seeks to develop mathematical models for allocation of critical resources during pandemics. Populating these instances with real-world data we would then develop novel algorithms to solve them
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system, including a suitable camera and an embedded system, will enable real-time acquisition of images of the tube carriage, from the side of the carriage, and subsequent image processing algorithms
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methods to improve the deployment, adaptation capabilities and safety of robots and critical infrastructures. The developed algorithms will be evaluated on legged robots, wheel-based robots and under
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context. The work will include, but is not limited to: investigating new mathematical formulations of the underlying physics; developing fast algorithms and numerical methods that leverage modern parallel
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analysed by bespoke machine-learning driven algorithms, combined with physical models, to de-noise images, identify features and correlate properties, giving critical insights into power loss pathways
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debugging and profiling Parallel numerical algorithms and libraries System software stack administration and novel/experimental hardware. Over the course of the appointment, the candidate will be supported
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, predictive maintenance algorithms, and digital twin technologies tailored specifically for healthcare, aviation, and sanitation industries. You will identify critical operational pain points within