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Field
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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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Mathematics, Applied Mechanics, or related disciplines (a minimum honours degree at UK first or upper second-class level) Experience in computational fluid dynamic/finite element modelling by using commercial
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develop AI- and deep learning–based computer vision tools to automatically identify and quantify intertidal organisms. Beyond computer vision, it will leverage machine learning for large-scale, data-driven
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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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provide powerful tools to improve the quality and efficiency of data-driven models. In parallel to the development of data-driven models for dynamical systems with geometric structures such as Hamiltonian
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, are crucial for modelling volcanic processes and are vital for understanding the transitions. Geophysical monitoring provides essential information to constrain these parameters and inform decision
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models. The project’s key objectives are to: 1) Identify critical indicators relating to ecosystem health and resilience; 2) Incorporate indicators into DBN models to simulate how ecosystems respond
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, the project accelerates trait data acquisition by applying computer vision to herbarium specimens and field photos, as well as large language models to extract complementary information from literature and
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to augment the funds to cover the extra costs associated with international student fees. Exceptional candidates may be eligible for an International Fee Bursary. Thermodynamic modelling of minority phases in
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-home rates. You will learn a wide range of molecular modelling techniques, as well as collaborative software development and computational skills providing expertise for a broad range of future careers