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cells; 2) Model AML plasticity at the single-cell level; 3) Propose candidate therapeutic targets for in vivo validation. The PhD student will be embedded in a collaborative and supportive team, working
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. He/she/they will learn and apply state-of-the-art molecular and cell biology technologies established in our team, ranging from in vivo disease models to multi-omics and single cell analysis
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, which will be used to implement high frequency and high efficiency IVRs for HPC applications. Objectives:-Fabrication, characterization and modeling of the composite magnetic materials.-Modeling
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For better or for worse, Generative AI is changing our world. A key challenge in Generative AI is many-shot jailbreaking—where a language model, despite being explicitly trained to reject harmful
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domains. The scientific outcomes are expected to be significant in: Earth system science – by improving models of Earth surface evolution and enabling better predictions of landscape response to climate
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one-fits-all model was proven unsuccessful. Large Language Models (LLMs) and knowledge graph models are expected to harmonize the formats and semantics but there are many open questions about their
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position will contribute to the research programme of the recently founded "AI Hub in Generative Models", a research consortium funded by EPSRC. The goal of the programme is to do research in the area of
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determine the impact of community acquired pneumonia that requires hospitalisation has on the quality of life of patients. The final stage will be to design a generic economic model to evaluate any new
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; radiopharmaceutical dosimetry with novel agents and/or software techniques; alpha particle RPT radiation biology modeling and analysis of clinical trial data. For additional information on a subset of expected
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nanoparticle systems. Investigate model particles such as liposomes, mesoporous silica and silver nanoparticles. Investigate RNA-LNP formulations for next-generation gene therapeutics, examining how lipid