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Field
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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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problem-solving skills and deep expertise in the development of complex computational models. Candidates who have not yet acquired their PhD would be appointed at the Research Assistant level. The
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, osteosarcoma) cell and time of origin is debated but experimental studies in different models suggest possible in utero induction with postnatal initiation similar to leukaemia. In Ewing sarcoma, FET::ETS gene
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(complexity). Develop and optimise a modelling pipeline including a decision support dashboard for optimal patient selection for surgery to ensure daily surgery caseload optimisation, post-operative care
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can be varied. Crucially, the models we derive will be validated by real-world measurements to ensure our simulation environments are realistic and scalable to more complex radar networks. This will
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modelling. This exciting project involves the application of innovative methods such as high-throughput experimentation to expediate the syntheses (and bioanalysis) of life-saving pharmaceuticals
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is characterised by complex and highly dynamic turbulent flows that define the performance and design of renewable energy systems and their infrastructure. This PhD project aims to enhance
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to the complexity of the mathematical models that describe them. The current consensus is that there are three “types” of viscoelastic chaos: modified Newtonian turbulence, elastic turbulence, and elasto-inertial
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treatment processes through advanced machine learning, validated against physics-based models and experimental data. System Integration: Integrating the DTs into material and energy balance equations
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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