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Applications are invited for a funded PhD studentship, supervised by Prof Andrew Dove (School of Chemistry) at the University of Birmingham (group website: http://www.dovegrouplab.com ). The project
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scientists. Applicants should have completed (or closer to completion) their undergraduate degree in Physics, Material Science, Physical Chemistry or related Physical Sciences (preferably with first-class
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probability, allow for the application of tools from probability theory to combinatorial problems and motivate the study of the typical properties of various combinatorial models, such as the Erdős–Rényi random
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Data-driven predictions of dynamical systems are used in many applications, ranging from the design of products and materials to weather and climate predictions. Mathematical concepts from geometry
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infrastructure where it is most urgently needed. Applicants should be comfortable working with quantitative analytical methods (specific machine learning skills can be developed during the PhD). Willingness
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://doi.org/10.1039/D2CC00532H ) that have potential applications in sensing, separations and catalysis. Our research focusses on three distinct challenges to achieving efficient material prediction: i
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data of indoor spaces and work with real-life scenarios. Informal enquiries can be directed to Dr Bruño Fraga (b.fraga@bham.ac.uk ) and Dr Isabel Morales-Muñoz (i.morales-munoz@bham.ac.uk ). Application
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involve experimental optimisation, leveraging computational tools, statistical modelling, and emerging AI/ML applications to streamline and accelerate the workflow for complex mixtures and metabolomics
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to moving or residing in the UK. International applicants must fulfil the University of Birmingham’s international student entry requirements, including English language. Further information: https
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additional costs relating to moving or residing in the UK. International applicants must fulfil the University of Birmingham’s international student entry requirements, including English language. Further