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for LLM reasoning applications in the future. The work will involve designing algorithms, running experiments on the HPC, analyzing the results and improving the algorithms. It will also involve extensive
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streams and generating high-fidelity synthetic populations for rigorous in-silico testing. Scientific Foundation Models & Continual Learning: Optimising LLM and agentic architectures for domain-specific
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multilingual AI, Translation quality evaluation using AI Teach undergraduate and postgraduate courses in Computational Thinking, Machine Learning and Natural Language Processing (NLP) for translators, LLM and
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Range $81,640-138,798/year Type of Position Staff Position Time Status Full-Time Required Education BS Click here for more information about equivalencies: https://hr.uky.edu/employment/working-uk
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implement cloud-native data pipelines connecting lab instruments, databases, and AI models Support model deployment, inference services, and experiment tracking (e.g., MLflow) Integrate LLM reasoning with
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intelligence solutions through applied research projects. Desirable Good knowledge in digital supply chain-related technologies such as AI, LLMs, Cyber Security, IoT, 3D printing, automation, supply chain
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an umbrella organization and builds on four pillars: Qualitative methods; Experimental methods; Computational Social Science, as well as Skill School (https://www.sam.lu.se/en/research/lund-social
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prior experience doing so is not required. Additional beneficial but optional experience and skills include multi-level modeling, LLM and/or NLP, behavioral coding, and/or psychophysiological monitoring
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learning Broad familiarity with geospatial programming libraries Preferred Knowledge, Skills, and Abilities: Non-LLM foundation model expertise Time Series Foundation Models Expertise with Graph transformers
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and their analytical frameworks. 2. Development of mechanisms for tuning Large Language Models (LLMs) and multi-modal foundation models to function effectively in resource-constrained environments. 3