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Grant and coordinated by the Principal Investigator (PI), Dr Federico Pianzola. This is an interdisciplinary project at the intersection of NLP, Digital Humanities, and Semantic Web technology. Millions
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techniques (e.g. explainable, ethical, empathic and agentic AI), natural language processing (NLP), large language models (LLMs), data science methods, and mHealth to analyze large-scale, multidimensional, and
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)-statistics, (applied) mathematics, or a related STEM field. Prior working experience with EHR data, machine learning, NLP, bioinformatics, and large language models (LLM) is preferred. In particular
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recently completed (or be close to completing) a PhD in Computer Science, Machine Learning, Natural Language Processing (NLP), or a related field, with a thesis focused on AI, specifically LLMs
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newly created division which focuses on development of novel data science methods to analyze biomedical big data for advancing health care. The Natural Language Processing / Information Extraction (NLP/IE
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, depression, and loneliness, and how mental health vulnerabilities increase susceptibility to polarization. Leveraging network science, NLP, behavioral sensing, and causal inference, the project pioneers new
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. This position will work closely with faculty in AI, NLP, Ethics, and Anthropology to design and conduct empirical studies, develop novel evaluation frameworks, and advance methods that ensure AI systems
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, NLP, behavioral sensing, and causal inference, the project pioneers new methods for detecting and mitigating online harms. Its results aim to inform public health, policy, and technology design
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. This position will work closely with faculty in AI, NLP, Ethics, and Anthropology to design and conduct empirical studies, develop novel evaluation frameworks, and advance methods that ensure AI systems
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rigorous, collaborative research aligned with project goals. Develop and apply deep learning models, particularly in computer vision, NLP, and multimodal systems. Publish in peer-reviewed journals and