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demonstrate: Essential Criteria: A PhD in Computer Science, specialising in Artificial Intelligence, Natural Language Processing Strong research background in NLP, LLMs. Experience with mechanistic
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-the-loop, decision-making for complex systems, optimisation for LLMs, foundation models, dimensionality reduction, deep learning, uncertainty quantification, language, and developmental robotics. About You
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experimentation in the area of Multi-agent Agentic AI systems applied to 6G network and service management. By leveraging recent advances in LLMs and agentic tools (MCP, LangChain, etc), the project will design
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to the teaching programmes in the LLB on International and European Law and potentially also in the LLMs on Public International Law, and International Human Rights Law. These appointments are teaching-only
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requirements: Candidates must hold, at the time of application, a Bachelor’s degree in Informatics Engineering or related fields. Candidates must also have knowledge in: i. Deep Learning and LLMs: practical
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models (LLMs) and prompt engineering/tuning for domain-specific applications. Essential Application/interview Ability to collaborate closely with international collaborators to deliver cross-disciplinary
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of running compact micro-LLMs directly on wearables. The overarching goal is to create scalable, ethical, and transparent personalization systems that support education and research. Funding The appointment
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Visiting Faculty, Lawyering Program - Cornell Law School Founded in 1887, Cornell Law School is a top-tier law school. We offer a 3-year JD program for about 200 students per class, a one-year LLM
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the registered research protocol; conducting case-based, qualitative comparative analysis (QCA), and LLM-assisted qualitative analyses; and leading the development of peer-reviewed manuscripts, public-use datasets
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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