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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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, 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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An understanding of optimization methods, either as applied to structural optimization problems or the underlying principles and algorithms for convex/integer programming. Essential Application/Interview The ability
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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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capabilities needed for truly sustainable operations. Research Question: How can AI-enhanced digital twin technologies with advanced optimisation algorithms transform manufacturing processes to achieve
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new brain stimulation methods, you will contribute to developing closed-loop algorithms for regulating brain dynamics with clinical applications in epilepsy and psychiatric disorders. Number of awards
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between advanced optimization algorithms and structural design. We are seeking a highly motivated and skilled postdoctoral researcher to join our internationally recognised group. You will join an active
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massive substrate profile datasets in high throughput; application of in-house machine learning algorithms to identify optimal linker activity and selectivity; synthesis and characterisation of linker
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during pandemics. Populating these instances with real-world data we would then develop novel algorithms to solve them. The selected candidate would disseminate their research by publishing in top-tiered