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Field
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to optimize metagenomic workflows across sample types, developing integrated, sample-specific methodologies. Collaborating with leading academic developers and front line metagenomics users, including
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designing and developing experimental equipment suitable for containing the liquids at the temperatures needed, as well as optimizing the quality of the data obtained, both through experiment design and
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effects of NSPs on poultry performance. Locally sourced ingredients are becoming more prevalent, challenging some of the traditional enzyme strategies in regard to substrate presence and ultimately, optimal
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optimization of batteries against the swelling phenomenon. This project aims at developing scientific machine learning approaches based on the Bayesian paradigm and electrochemical-thermomechanical models in
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project offers a unique opportunity to develop a cutting-edge genomic epidemiology toolkit for real-time fungal surveillance. You’ll optimize DNA extraction protocols using advanced enzyme-based methods
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in a more accurate analysis of optimizing the service performance. Computer vision approaches such as ones for object identification and action recognition can help to automatically identify deviations
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to developing novel computational methods for design and optimization problems in turbomachinery with strong support from Rolls Royce plc. The student will be expected to closely work with Rolls Royce Engineer
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through advanced modelling and simulation. A key objective is to validate and optimize poroelastic finite element models of brain tissue, making them more accurate and clinically relevant. Additionally
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optimal operating conditions and followed by surface analysis techniques (e.g. Scanning electron microscope, X-ray diffraction for residual stress measurements, Electron Back-Scattered Diffraction and
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varying coolant chemistries, the study aims to understand the effects of deposited CRUD on surface morphology and thermal performance. The project employs a comprehensive approach integrating experimental