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Center for Drug Evaluation and Research (CDER) | Silver Spring, Maryland | United States | about 4 hours ago
language processing (NLP) to automate FDA’s review of these qualitative responses, potentially providing both more accurate and efficient review of consumer data. Learning Objectives: Under the guidance of a mentor
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-mediated problem by distinguishing failures at the feedback source, during signal transmission and during model updating. In this project, we consider Biomedical NLP as a domain that provides a demanding
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of Information and Computing Sciences at Utrecht University. The Natural Language Processing group covers both symbolic and statistical approaches to NLP, with particular strengths in explainability, natural
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We are seeking a highly motivated Research Associate in NLP, Mechanistic Interpretability and Trustworthy Generative AI. This role offers an exciting opportunity to contribute to AIRIS: Mechanism
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24 Jul 2026 Job Information Organisation/Company Utrecht University Research Field Computer science » Informatics Computer science » Programming Language sciences » Linguistics Researcher Profile Recognised Researcher (R2) Application Deadline 11 Sep 2026 - 21:59 (UTC) Country Netherlands Type...
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retrieval or natural language processing (NLP) research. Set within the Interaction, Technology and Information Discipline, and reflecting a strong human–computer interaction orientation, the successful
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10 Jul 2026 Job Information Organisation/Company CNRS Department Groupe de recherche en Informatique, Image, Automatique et Instrumentation de Caen Research Field Engineering Computer science Mathematics Researcher Profile First Stage Researcher (R1) Application Deadline 30 Jul 2026 - 23:59...
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: to make the world of tomorrow safer. Be part of change Implementation of Natural Language Processing (NLP) approaches, including: Feature extraction (LLM-supported, embedding-based as well as "classical
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FL; 3) Design and optimise task-specific FL algorithms for NLP and Medical AI; 4) Design and implement a user-friendly FL framework for both research and technology adoption purposes. We expect
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Background and Motivation Modern deep learning models have achieved remarkable success in computer vision and natural language processing. However, they typically produce overconfident predictions and lack reliable mechanisms to quantify uncertainty. This limitation becomes particularly...