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such as micro-XRF, synchrotron diffraction, SIMS, and 3D X-ray CT, it will reveal how variations in composition, microstructure, and metal-making processes shape an object's unique metal pedigree
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. Supervisor Bio I’ve been working in the field of Bayesian ML for 10+ years, with a focus on real-world applications and have developed several insect tracking techniques. As well as an opportunity to conduct
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PhD: Digital Optimisation of Rail Grinding EPSRC Centre for Doctoral Training in Machining, Assembly, and Digital Engineering for Manufacturing PhD Research Project Directly Funded UK Students Dr
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health. You will develop and apply cutting-edge machine-learning techniques to identify the most informative indicators of ecosystem change and use them to build dynamic Bayesian network (DBN) ecosystem
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Exactly: A Bayesian Approach. The project aims to address the challenges in pooling inference, by developing and implementing either exact or asymptotically exact Monte Carlo algorithms in collaboration
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opportunity for a highly motivated and skilled Research Associate/Assistant in statistics to join the EPSRC funded project PINCODE: Pooling INference and COmbining Distributions Exactly: A Bayesian Approach
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learning, evidence synthesis in public health and statistical genetics and genomics. We are recognised for our strength in Bayesian inference applied to biomedicine and public health. The MRC Biostatistics
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perception of object shape and its encoding in languages across the world. The successful candidate will work with Prof. Larissa Samuelson on a longitudinal study tracking how children from 24- to 42-months
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ecology and oceanography, the project will leverage large existing datasets on (i) the movement of migratory seabirds throughout their annual cycle, available via BirdLife’s Seabird Tracking Database (STD
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ability to evaluate fossil fuel CO2 (ffCO2) emissions is currently limited. ‘Bottom-up’ emissions estimates, based on inventory-style accounting and mobile tracking data, can differ significantly from each