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to apply. This integrated pipeline spans: continuous clinical genomic data re-analysis → massive parallel clinical biomarker postprocessing → clinical NLP and LLM tool development (history-taking, visit
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accurate and relevant outputs. Conducts testing and iterative improvements to optimize LLM performance. Leverages expertise in machine learning, natural language processing (NLP), and multimodal AI
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of Learning Analytics tools and processes to inform learning analytics design plans and design strategy, such as Social Networking Analytics (SNA), Natural Language Processing (NLP), Educational Data Mining
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Natural 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
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(Non-Profit Success Pack) and architecting schemas specifically within a Snowflake environment. AI & NLP: Experience using LLMs (OpenAI, Anthropic, or open-source equivalents) for AI-driven text
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models (e.g. NLP‑based classification, embeddings, or tree‑based models) within agreed project scope and under direction. Work with structured and geospatial datasets, including maintaining and querying
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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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, model training, validation, deployment, and monitoring in production. Natural Language Processing: Advanced knowledge of NLP techniques and large language models (LLMs), including prompt engineering
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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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providing technical input for international and national proposals. Participate in training activities, workshops, and the CoE’s AI capacity development. Where to apply Website https://karjera.ktu.edu/en-GB