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and sustainability; Investigate and apply artificial intelligence and machine learning techniques, including large language models (LLMs), across CENSE’s scientific body in its five thematic areas
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: Advancing machine unlearning, privacy-preserving techniques, and robust data curation. AI Safety: Ensuring robust alignment and safety in multi-agent LLM systems Efficiency: Streamlining large-scale model
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: Advancing machine unlearning, privacy-preserving techniques, and robust data curation. AI Safety: Ensuring robust alignment and safety in multi-agent LLM systems Efficiency: Streamlining large-scale model
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combinations that support the creation of innovative and sustainable food products. Another example is using large language model (LLM) tools to automatically extract and structure fragmented information from
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technologies in NLP, LLMs, and RAG. Programming skills in Python, including experience with machine learning libraries (e.g., PyTorch, Scikit-learn, Hugging Face Transformers) and development tools (e.g., Co
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technologies in NLP, LLMs, and RAG. Programming skills in Python, including experience with machine learning libraries (e.g., PyTorch, Scikit-learn, Hugging Face Transformers) and development tools (e.g., Co
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technologies in NLP, LLMs, and RAG. Programming skills in Python, including experience with machine learning libraries (e.g., PyTorch, Scikit-learn, Hugging Face Transformers) and development tools (e.g., Co
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develops LLMs and agentic AI systems for scientific discovery, engineering and physical systems. We investigate how AI can reason about scientific problems, interact with simulation software and support the
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computational and energy costs of LLMs, this work will focus on smaller, domain-specific models. Where to apply Website https://emploi.cnrs.fr/Offres/Doctorant/UMR8254-SYLDES-026/Default.aspx Requirements
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correlated materials. If time allows, as mentioned before, there is also the possibility to address LLM and chemistry with very similar approaches Where to apply E-mail [email protected]