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Field
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This PhD project will focus on developing, evaluating, and demonstrating advanced data analytics solutions to a big data problem from aerospace or manufacturing system to uncover hidden patens
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statistical methods are not suitable for big data due to their certain characteristics: heterogeneity, statistical biases, noise accumulations, spurious correlation, and incidental endogeneity. Therefore, big
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ADM, one of the worlds largest food ingredient suppliers, this PhD program will explore the impact of novel milling technologies on microbial accessibility of carbohydrates in food ingredients. Using
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narrow down what parts of our genome are actually important for defining modern human-specific biology. This project will analyse data from these ultra-large datasets, alongside data from our great apes
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melanogaster. This project will take the next big step: moving from finding sexually antagonistic genes to uncovering what makes them special, how they affect fitness and life history traits, and the molecular
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Start date 1 October 2026 Additional Funding Information This project is awarded with a 4-year Norwich Research Park Biosciences Doctoral Training Partnership PhD CASE studentship with Inspiralis Limited
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create a working framework that includes both experimental and modelling prototypes, including AI/ML tools to assist with the large number of variables involved. This project is seeking candidates with a
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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
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experimental chemistry. Additional training in a wide range of soft and hard skills is available at the University. What you will do: This PhD project aims to bring together multi-scale modelling and data-driven
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Please note, this is a PhD Scholarship co-funded by Foundations, the National What Works Centre for Children and Families and the biggest funder of evaluation research in early interventions