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Field
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and non-hazardous agents to the Institutional Biosafety Committee (IBC) as well as all animal protocols to the Animal Care Committee (IACUC) as requested by the Director. About the School and Department
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-cell depleting agents. The aim of the project is to develop tools that allow monitoring of disease-relevant B-cell populations through B-cell depletion therapy and to assess correlations between presence
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Multimodal Models Generative AI, Agentic AI, Physical AI, and Embodied AI Trustworthy AI, including explainability, auditability, and privacy Edge AI and model optimisation Physics-informed neural networks
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timely research question: How can Large Language Models (LLMs) and intelligent agents support transparent, scalable, and auditable clinical data harmonization? We are particularly interested in: LLM-driven
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areas: Computer Vision and Image Processing Machine Learning, Deep Learning, and Reinforcement Learning Large Language Models (LLMs) and Multimodal Models Generative AI, Agentic AI, Physical AI, and
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agents. Participate in fundamental studies of entomopathogen biology and ecology to better understand their mechanisms and environmental interactions. Collaborate with research team members and
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(potentially based on AI agents) capable of coordinating both tools, deciding when to trigger drone inspections, and synthesising maintenance recommendations with precise spatial localisation. BINDING
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: Probabilistic generative models (VLMs, diffusion, flow models) Reinforcement learning & Markov decision processes Causal inference & counterfactual reasoning Mechanistic & physics-informed modeling Agentic AI
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agent based/individual based modelling, SEIR modelling, geospatial statistics, Bayesian statistics, burden mapping, measuring the impact of the environment on disease among others. The PI has projects in
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therapeutic targets associated with the response to new antitumor agents. Participation is also expected in the implementation and optimization of experimental methodologies, the integrated processing and