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conversational guides for enhancing visitors’ learning and experiences in public educational environments. The PhD student will focus on addressing the challenge of visual blindness in large language models (LLMs
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Science, Statistics, Applied Mathematics, or a related field. • Strong background in convex analysis, statistical machine learning (reinforcement learning, LLM and generative modeling), stochastic modeling and
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prior experience in at least three of the following areas: Python programming Develop LLM-based tools to automate data connector generation for data ingestion. Design and implement a multi-layered storage
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace – In Partnership with Rolls-Royce PhD
aerospace environments. The objectives of the PhD are: •Extract structured engineering knowledge from unstructured maintenance data using LLMs, and represent it using ontologies and knowledge graphs •Develop
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to reason about software (e.g., LLM agents for finding and fixing bugs) Static and dynamic program analysis (e.g., to infer specifications) Test input generation (e.g., to compare the behavior of old and new
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, sentiment analysis and artificial intelligence (particularly LLM) API integration Familiarity with grant writing and funding acquisition is desirable. Benefits Eligibility YES FLSA Status Exempt Apply now
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: https://ieeexplore.ieee.org/document/9415623 ) 5. Adversarial attacks on Large Language Models. (Reference: https://lilianweng.github.io/posts/2023-10-25-adv-attack-llm/ ) Before you apply Prospective
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LLM, VLM and embodied AI, with specific applications to collaborative interaction with people. You will be supervised by Prof. Tony Belpaeme (www.tonybelpaeme.me) and will be part of a vibrant and