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, allowing them to add to their existing clinical targets of anxiety and depression disorders, thus developing impact from this research. Methodology This studentship will take a mixed-methods approach to
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This self-funded PhD opportunity sits at the intersection of several research domains: multi-modal positioning, navigation and timing (PNT) systems, AI-enhanced data analytics and signal processing
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information about the role, please click on the apply button above. Please provide a CV and 1-page covering letter, along with contact details of 2 referees. The covering letter should indicate how you meet the
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microenvironment (TME), affecting immune cell signalling in ways that can either promote or inhibit tumour growth. While several clinical and preclinical trials have explored radioimmunotherapy, success has been
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challenging properties of uncertainty, irregularity and mixed-modality. It will examine a range of models and techniques that go beyond Markovian approaches, including state-space models, tensor networks, and
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mixed-modality. It will examine a range of models and techniques that go beyond Markovian approaches, including state-space models, tensor networks, and machine learning frameworks such as recurrent
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at the interface between stochastic modelling, signal processing and data science. Ultimately, the project will develop key indices that can be used to assess the health of the soil ecosystem. Such indices
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management—are encouraged to apply. Methodological approaches are flexible and may include qualitative, quantitative, or mixed methods, depending on the research focus. Exemplary research topics include (but
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experience relate to the project. Highlight your experience in modelling, signal processing and neural data analysis. The studentship code BI095 in the ‘Studentship/Partnership Reference’ field When prompted
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, develop business cases and more. At the 6-month point, students progress onto their interdisciplinary PhD research project, supervised jointly by two academics from two research groups. Usually, supervisors