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Field
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: Artificial Intelligence / Machine Learning Knowledge Representation and NLP methods Clinical Informatics Bioinformatics Biomedical Ontology Public Health Informatics Nursing Informatics Imaging Informatics
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, preferably Python and experience with frameworks such as TensorFlow or PyTorch. Mentoring: The primary supervisor, Dr. Hua Xu, is a well-known researcher in clinical NLP. The postdoc will be directly mentored
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 12 hours ago
is available at UNC under Prof. Mohit Bansal in the UNC-NLP Lab. The focus of this NLP+ML postdoc position will include, but is not limited to, multimodal+embodied semantics, human-like language
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degree in Physics, Materials Science, Computer Science, Data Science, or related fields Proven experience with large language models (LLMs), natural language processing (NLP), and fine-tuning techniques
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associate position with a focus on natural language processing (NLP). This extremely fast-moving and competitive field has produced innovations with highly visible impact in industry, education, and public
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language processing (NLP) to augment clinical decision-making and expand access to high-quality healthcare. Our lab develops new methods to improve model trustworthiness and leverages heterogeneous clinical data
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associate position with a focus on national security applications of natural language processing (NLP). This extremely fast-moving and competitive field has produced innovations with highly visible impact in
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proposals and reports. Minimum Qualification Ph.D. from an accredited institution in Computer Science, Electrical and Computer Engineering, or a related field with a focus on AI, NLP (natural
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: Artificial Intelligence / Machine Learning Knowledge Representation and NLP methods Clinical Informatics Bioinformatics Biomedical Ontology Public Health Informatics Nursing Informatics Imaging Informatics
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, aggregation, linking and retrieval of comprehensive heterogeneous and distributed data sources. To this end, both statistical and linguistic analysis methods (NLP) as well as machine learning in combination