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transparency. Application areas include FinTech, embedded systems (e.g., mobile), business or entertainment systems, cybersecurity, and more. For more information, you may refer to https://www.uni.lu/snt-en
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ML systems into production environments, with a focus on performance, robustness, and scalability. Domain expertise in NLP, computer vision, or speech processing. Proficient in Python for software and
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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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the context of this scholarship include: - researching and understanding recent innovations in the field of natural language processing (NLP), LLMs and AI agents - researching methodologies for analysing and
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. Knowledge of academic library functions. A well-qualified candidate may also possess: Knowledge or familiarity with AI-enhanced tools or emerging technologies such as generative AI, NLP tools, and research
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Language Processing (NLP), as well as other industry technology trends, to recommend innovative solutions. Collaborates with business stakeholders to identify opportunities for AI/ML adoption and translate requirements
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units centered around AI and technology-enhanced learning, such as the Institute for Advanced Learning Technologies (https://ialt.education.ufl.edu ). Successful applicants for the tenure track Assistant
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more. For more information, you may refer to https://www.uni.lu/snt-en/research-groups/trux/ . The successful candidate will: Conduct cutting-edge research in multimodal and multilingual natural
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methods to biological problems Experience with database querying, management systems, and data extraction techniques for large datasets Knowledge of natural language processing (NLP) and/or large language