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Job Description To perform work on applying large language models (LLMS) and related software to affordance reasoning in the area of robot imagination and Real2Sim2Real transfer. The use of discrete
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of Computing, to work on large language models, with application to text summarization. The initial appointment is for a period of one year, with possible extension subject to research funding availability
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, model building, and management of research projects. If you have a background in computer science and a strong interest in medicine and large language models, this position may be ideal for you
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learning/analysis. Prior research experience and track record in R&D and standardization. Prior experience in state-of-the-art AI techniques. Mastering of a programming language would be valued (e.g. Python
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aiding fuzzing techniques with large language models. Tasks Conduct Research on AI-Aided Fuzzing: Lead research efforts to explore the integration of large language models (LLMs) with fuzzing techniques
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research experience in machine learning, deep learning, computer vision. Mastering of a programming language would be valued (e.g. Python, Matlab…) Self-driven, highly motivated, with interest to work with
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to teacher education, ELL is dedicated to innovative teaching and high-quality research in the areas of English language and linguistics, literature, and English teacher education. We have a strong and diverse
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fluent 2nd language (Mandarin, Bahasa Indonesia, Tagalog, Arabic), would be an added advantage • Excellent coordination and organization skills, with a customer-centric mindset • Self-motivated