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scientific discoveries explore and evaluate usability of system architectures such as Retrieval-Augmented Generation (RAG) for data retrieval and knowledge inference implementation of your machine learning
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programme at the Faculty of Science . The ideal candidate has a background in or experience with one or more of the following topics: Advanced deep learning architectures Mathematical foundations of machine
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development. Using cutting-edge technologies, the project aims to investigate how three-dimensional changes in PU.1 chromatin architecture influence cell fate decisions and leukemia development. Applicants
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with SQL and basic database concepts Desirable: Experience with LLMs, NLP, embeddings, semantic search, or generative AI Familiarity with RAG architectures, vector databases, or knowledge-enhanced AI
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bright minds to tackle advanced topics such as Advanced Database Management Systems, AI, Edge-Fog-Cloud Architectures, and Data Analysis applied to real-world agricultural challenges. We are recruiting