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include but are not limited to: AI-driven design workflows; machine learning and generative AI models; AI-based performance evaluation and simulation; agentic and multi-agent AI systems; human-AI
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prompt design as a controlled manipulation, generative voice agent pipelines, conversation logging and transcription Extending and validating existing LLM based coding pipelines for transcript derived
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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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infrastructure for these studies, including prompt design as a controlled manipulation, generative voice agent pipelines, conversation logging and transcription Extending and validating existing LLM based coding
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noncrystalline biological and materials systems; NMR-based studies of antibacterial agents, their interactions with bacterial cells, and their mechanisms of action; and Integration of NMR with complementary
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application consists of: An application Transcript(s) – For this opportunity, an unofficial transcript or copy of the student academic records printed by the applicant or by academic advisors from internal
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how AI is changing work. Its projects examine what happens when generative and agentic AI enters leadership, everyday workflows, team communication, professional learning and career decisions. Across
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application consists of: An application Transcript(s) – For this opportunity, an unofficial transcript or copy of the student academic records printed by the applicant or by academic advisors from internal
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chemistry, and artificial intelligence. This position offers an exciting opportunity to advance fundamental understanding of heterogeneous catalysis through both first-principles simulations and the
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prioritise RD as a mechanism for ecosystem resilience. The project will use Agent-Based Policy Modelling (ABPM) to simulate how actors such as land managers, farmers, local authorities, and conservation