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contributing to our clinical NLP tools, algorithms and interfaces used by clinical specialists. The post holder will be expected to contribute to: Extend our software platforms for electronic healthcare record
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-resource settings. This project aims to achieve several objectives, including the development of a new AI-algorithm and a paired dataset for comparing how different imaging techniques influence
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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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About us: We are seeking experts in medical image deep learning to join our team and help develop novel computationally efficient segmentation algorithms. We welcome application from individual with
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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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at the interface between computational design and in vitro experiments, the team has developed multiple in silico and in vitro methods to design novel antibodies and nanobodies as therapeutic agents and research
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considered for this project. Application form Closing date 14 March 2022 Decision date May 2022 Additional information ¿Multi-criteria Automatic Algorithm Configuration under Streaming Problem Instances
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physical laws, or an implicit form of extra data examples collected from physical simulations or their ML surrogates. In medical domains, patient data is typically distributed across multiple hospitals
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will include contributing to our clinical NLP tools, algorithms and interfaces used by clinical specialists. The post holder will be expected to be able to contribute in the following areas: Extend our
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control laws into Trent gas turbine engines and developed algorithms monitoring fleets of 100s of engines flying all around the world. During the PhD, you will have the opportunity to deeply engage with