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Field
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. Generative AI and AI agents are rapidly changing how software-based systems are being designed, developed, and evaluated. While AI agents have become common in certain Software Engineering tasks, such as
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agents for the imaging of solid tumours. Project Overview The successful candidate will contribute to the design, synthesis, and evaluation of innovative tumour-targeting contrast agents for applications
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changing work. Its projects examine what happens when generative and agentic AI enters leadership, everyday workflows, team communication, professional learning and career decisions. Across the network
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robotics. Specific application areas of focus are long-term autonomous missions in large and uncertain environments, semantic mission planning with foundation models, agentic task decomposition and event
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robotics. Specific application areas of focus are long-term autonomous missions in large and uncertain environments, semantic mission planning with foundation models, agentic task decomposition and event
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: Advancing machine unlearning, privacy-preserving techniques, and robust data curation. AI Safety: Ensuring robust alignment and safety in multi-agent LLM systems Efficiency: Streamlining large-scale model
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lessons from experiments and experience to shape AI-native software engineering pilot and transition improvements with organizations and measure their success create novel agents and agentic workflows
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lessons from experiments and experience to shape AI-native software engineering pilot and transition improvements with organizations and measure their success create novel agents and agentic workflows
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: Advancing machine unlearning, privacy-preserving techniques, and robust data curation. AI Safety: Ensuring robust alignment and safety in multi-agent LLM systems Efficiency: Streamlining large-scale model
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agentic software can change the way scientists interact with complex imaging pipelines – for example, by allowing users to formulate analysis tasks at a high level while software agents orchestrate