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critical computing. High-level topics include: social identity cues in the design of LLM-based chatbots or social robots trust and reliance on conversational agents designed to be charming and disarming so
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that are conducive to successful completion of the problem at hand. Particular focus will be on multi-robot and multi-agent problems (e.g., navigation, cooperative transport, team-based agent games). The ideal
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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
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engineered mouse models for the depletion of different CAF populations, in vitro three-dimensional pancreatic tumour organoid/fibroblast co-culture models, CRISPR-based technologies, bulk and single-cell RNA
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the combined themes of human-computer interaction and critical computing. The lab will be exploring the notion of "deceptive by design" on all fronts: social identity cues in the design of LLM-based chatbots
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wet- and dry-lab scientists that are studying RNA, chromatin and transposon biology, covering all aspects of this RNA-based immune system, including the biogenesis of small non-coding RNAs and the
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learning and AI models to imaging data [3]. The student will be tasked with the development of new models for the early detection of CIN cancers, applying bleeding edge computational methods and machine
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mouse models and immunology expertise (CRUK-CI), access to relevant patient material (matched fresh-frozen PDAC and serum samples). We will utilize AstraZeneca expertise in spatial and circulatory
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prostate cancer risk across diverse ethnic groups. This work aims to support more equitable risk stratification in cancer screening programmes. Using simulations based on multistate modelling framework
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on cell viability and DDR activation in established human cell models. The student will perform CRISPR screens to determine factors that affect resistance/sensitivity and follow these up with mechanistic