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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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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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Intelligence (AI). Despite recent advances in data-based AI (e.g., deep learning and LLMs), knowledge-based methods are still state-of-the-art when it comes to building reliable and explainable decision support
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PhD Studentship: Open Radio Access Network (ORAN) for Distributed Edge Computing Orchestration in 6G
Language Models (LLMs). Orchestrating AI/ML pipelines in 6G. Developing certification and checking processes for code inside ORAN 6G. The research will be a combination of software engineering, radio
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. Examples of topics include algorithmic fairness in network analysis, developing network embedding frameworks for real-world network datasets or AI models based on agentic LLMs for simulating real-world
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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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Models (LLMs). Orchestrating AI/ML pipelines in 6G. Developing certification and checking processes for code inside ORAN 6G. The research will be a combination of software engineering, radio
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algorithms, have excelled in tasks like computer vision, image recognition and large language models (LLM). However, their reliance on extensive computational resources results in excessively high energy
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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