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) promise personalized learning in a more natural way. In particular, leveraging the natural language capabilities of large language models (LLMs) - a type of gen AI – to enable dialogic practice is a
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implementation novel machine learning and large language model (LLM) algorithms for Green AI applications. Support the research of efficient AI techniques, including model optimization, parameter-efficient fine
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. Experience of current Artificial Intelligence and Machine Learning methodologies/tools e.g. agentic patterns, LLM orchestration, vision models etc. Desirable Criteria: MEng, MSc or Ph.D. in a relevant area
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evaluate statistical and machine learning models - Publish results in peer-reviewed journals Desired Qualifications - Master’s degree in statistics, mathematics, data science, bioinformatics, physics
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machine learning, topological quantum materials, and/or related areas. The successful candidate will have access to HiPerGator, the fastest university-owned supercomputer in the United States (TOP500
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In this position, you will join our Simulation and Data Lab for AI and Machine Learning for Remote Sensing . The lab advances interdisciplinary research and operational services by combining
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or similar. They will have in-depth knowledge of and demonstrated experience of current models for deep learning and machine learning, and strong quantitative (in silico) analysis skills and experience using
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) promise personalized learning in a more natural way. In particular, leveraging the natural language capabilities of large language models (LLMs) - a type of gen AI – to enable dialogic practice is a
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* Under the guidance of the professor, students will contribute to: Curate and analyze datasets of superionic conductors' structures and properties. Build and train machine learning models (especially graph
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models. This role is ideal for those who have a demonstrated history in collaborative research, effective communication, the ability to follow standard protocols, and an aptitude for troubleshooting