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PhD Studentship: Designing Human-AI Teams for Meaningful Human Control of 'Machine-Speed' Operations
participants interact with AI agents (e.g., developed using CrewAI or similar platform) and will run in teams of 4-6 agents (human or AI), e.g., the teams could be all human, all AI, or combinations
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chemical warfare agents (CWAs), allowing for safe working outside of the lab. However, it is currently poorly understood how to model the interaction of CWAs with supramolecular hosts with respect
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increasingly threatened by plant diseases, insect pests, climate change, and growing pressure to reduce chemical inputs. Understanding how multiple biological threats interact within crops represents one
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mathematics. You will undertake a single, ambitious research project: to begin the formalisation of the local Langlands correspondence for GL₂(F) in the Lean interactive theorem prover by leveraging AI agents
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increasingly threatened by plant diseases, insect pests, climate change, and growing pressure to reduce chemical inputs. Understanding how multiple biological threats interact within crops represents one
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of rice is caused by blast fungus (Magnaporthe oryzae), which also is the causal agent of the recent wheat blast outbreak in Asia. Rice blast infections start when spores land on leaf surfaces, attach and
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. These differences introduce distribution shifts that can degrade model performance and reliability over time, particularly in “one-to-many” supervision settings where a single human operator oversees multiple agents
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mathematics. You will undertake a single, ambitious research project: to begin the formalisation of the local Langlands correspondence for GL₂(F) in the Lean interactive theorem prover by leveraging AI agents