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Field
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will be grounded in rigorous mathematics coupled with a sound understanding of the underlying earthworm ecology. Bayesian inference methodologies will be developed to estimate where and when behavioural
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are suitable. The aims of this project are to Review operating characteristics proposed for rare disease trials Develop novel Bayesian operating characteristics for different types of rare disease trials Apply
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for health policy decision-making, these methods will be developed using a Bayesian framework. This PhD project will deliver a substantial contribution to original research in the area of health data science
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We are seeking an enthusiastic and capable individual to join our team as a PhD researcher in developing instrumentation and simulations to monitor and track satellites. The successful candidate
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for health policy decision-making, these methods will be developed using a Bayesian framework. This PhD project will deliver a substantial contribution to original research in the area of health data science
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Background Network Rail operates several telecom networks which provide connectivity for various signalling systems. Therefore, the performance of telecoms assets is integral to how the railway system operates
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will be grounded in rigorous mathematics coupled with a sound understanding of the underlying earthworm ecology. Bayesian inference methodologies will be developed to estimate where and when behavioural
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system using deep learning (DL). The project’s objectives include generating training data from synthetic datasets and real-world images (cadaver and actual intraoperative THR images), developing a marker
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. when do we stop modelling? How do we track / score the quality of the model? What is the required level of quality over time? How can quality be brought to the required level? Can Machine Learning, Large
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Almost all radar systems currently transmit from the same location. This kind of radar modality has been optimised for decades, however the challenge to detect very small and very fast objects