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leveraged to accelerate learning from both classical and quantum data. The project will develop rigorous theoretical frameworks to understand key properties of quantum machine learning models—expressivity
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of fungal pathogens. The successful candidate will make extensive use of a range of in vivo models of fungal infection and will have access to the wide range of transgenic tools and in vivo immunology
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Fixed Term Contract for 24 months We welcome applications from passionate and skilled post-PhD or experienced researchers in malacology, epidemiology, schistosomiasis modelling, or spatial data
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remission as a model of flare vs remission with a 50% relapse rate. Initial data analysis has taken place using the 10x Chromium single cell sequencing identifying putative cellular subpopulations
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this aim and to collectively, and individually, make a real difference. The role An exciting opportunity for a postdoctoral Research Fellow with a background in mathematical modelling / epidemiology has
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/rehabilitation applications. It is expected that the application has the knowledge of: 1) deep learning, large AI models, large language models; 2) the rendering techniques for generating human body animations
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can successfully predict previously-unknown regulators of seed development through functional genetic analysis of conserved, uncharacterised genes in the model seed plant Arabidopsis thaliana
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modelling; Coordination of field measurement and data analysis; Writing reports and publications; Supporting project team and organising project meetings; The project includes generous equipment budget and
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and healthcare system simulation modelling will be useful for evaluating these options. To that end, this team will develop a novel analytical simulation framework and use it to address these pressing
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, and computer modelling skills. Excellent interpersonal communication and oral presentation skills in English Self-driven and strong team spirit Open to fixed-term contract (renewable upon review