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to generate tools and techniques to simulate HIV infection dynamics using a multiscale agent-based modelling technique (cells, viruses, drugs, antibodies, human lymph system, seconds, days, years). This project
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fungal infections. Emerging research is exploring radiometals conjugated with targeting molecules for in vivo imaging of infections via PET or SPECT. These agents can also be linked to therapeutics
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fungal infections. Emerging research is exploring radiometals conjugated with targeting molecules for in vivo imaging of infections via PET or SPECT. These agents can also be linked to therapeutics
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networks continuously generate sensitive data. You will investigate adaptive learning frameworks – such as multi-agent or multi-task approaches – that ensure robustness, explainability, and trust across
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to prostate cancer progression. This information will support the setting up of a clinical trial where anti-microbial agents are used to prevent prostate cancer development, resulting in significant
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health, and bioinformatics. You will apply advanced AI methods - from classical machine learning to large language models and agent-based AI - on large-scale healthcare datasets, including structured
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from the Newcastle Urban Observatory, public transport ridership data, questionnaires and travel surveys, and the DARe MATSim agent-based modelling suite, this PhD will seek to gain a deeper
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infinite extent models and limited extend data based on trust over particular sets, and naturally create explainable AI structures which can further be analysed from a verification and validation perspective