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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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tumours and metastases with the goal to design combinatorial therapeutic approaches. The project will involve the use of genetically complex organoid-derived transplantation mouse models of pancreatic
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functional polymer strands into these DNA devices, which allows them to respond to light, heat, or chemical environment. In this project you would design, construct, test, model, and develop DNA-polymer hybrid
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is characterizing the solid-state landscape of drug candidates, which can involve complex solid-phase transitions such as the dehydration of hydrates, desolvation of solvates, and solid-solid phase
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identifications from the synchrotron X-ray data. The data acquired will be compared with existing transformation kinetics models to assess their reliability and, where necessary, will provide the data needed
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for complex data accessible to the scientific community and to produce innovative methodology related to trial designs, longitudinal and event history data, precision medicine, causal inference, AI/machine
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processes associated with CIN [1], leveraging single-cell DNA sequencing understand CIN heterogeneity [2], and development and implementation of machine learning and AI models to imaging data [3]. The student
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: Advanced molecular and protein analysis Mass spectrometry-based imaging Multi-omics technologies Preclinical cardiometabolic animal models They will also gain professional development in data stewardship
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mouse models and immunology expertise (CRUK-CI), access to relevant patient material (matched fresh-frozen PDAC and serum samples). We will utilize AstraZeneca expertise in spatial and circulatory
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microscopies, ultrafast photophysics, X-ray, THz, superresolution, modelling. Further details including funding information is available at: www.nanodtc.cam.ac.uk/apply/ For entry in October 2026, applications