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to quantify the phase fractions and lattice parameter evolution, which in turn will allow quantification of the phase transformations taking place. This approach has advantages over other methods as it utilises
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will be tasked with the development of new models for the early detection of CIN cancers, applying bleeding edge computational methods and machine learning approaches to improve detection and
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independent researcher. We welcome applications from students who wish to apply innovative statistical methods to real biomedical problems in order to deliver key insights into human health and disease. Three
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the proteins associated with their binding sites with a view to understanding therapeutic mechanisms [e.g. see Nature Biotechnology 2023, 41 1265]. We are expanding this work to create methods to characterise
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production processes and are actively exploring the incorporation of new materials, technologies and designs in their operations to achieve zero-carbon construction elements. The construction industry is under
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situ, with direct structure determination, and (ii) investigating and optimizing methods for chirality determination using electron crystallography. Candidate We are looking for a highly motivated and
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technologies, bulk and single-cell RNA-sequencing, flow cytometry, multiplex immunofluorescence, and standard molecular biology and biochemistry techniques. A computational component may also be available
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of our approach is the innovation of novel methods to investigate genome function. For example, we have recently developed ways to map the binding of nucleic acid-interacting drugs and small molecules
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both sites. The project sits at the interface of cell line engineering, protein science and machine learning and you will receive advanced training in these areas while developing methods to accelerate
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on the research topic and relevant methods. By the second half, the candidate will take on a leading role and begin carrying out the research comprising their doctoral dissertation. The candidate is expected