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language processing, machine learning, artificial intelligence, and human-computer interaction. Established within the School of Computer Science, LTI pioneers innovative ways to understanding, processing, and
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in bioinformatics, machine learning, single-cell omics, statistics, or genomic medicine, and a keen interest in obesity, diabetes, and cardiovascular disease. Background The Novo Nordisk Foundation
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(SHORES) and the Division of Engineering, New York University Abu Dhabi, seek to recruit a Postdoctoral Associate to work on a fascinating project focused on the development machine-learning powered digital
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satisfactory performance and availability of funding. Research topics of interest include numerical methods for scientific machine learning and AI, and their applications to various science and engineering
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on the true, astrophysical candidates is a computational needle in a haystack. To tackle these “big data” challenges, astronomers have begun to employ machine learning techniques. The application of machine
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Vacancies Postdoc position on Federated/Continual Learning for Time-Series IoT Data (TRUMAN Project) Key takeaways In this role, you will address the intricate challenge of enabling AI to learn
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(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. The candidate will apply
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well as familiarity with machine learning workflows, natural language processing (NLP), and text-as-data methods. We are especially interested in applicants who demonstrate a strong substantive interest in using
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National Aeronautics and Space Administration (NASA) | Huntsville, Alabama | United States | about 5 hours ago
to advance use of foundation models for Earth Science research and applications, including fine-tuning experiments Use of remote sensing, models, and/or machine learning to further our understanding
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models that merge machine learning techniques with mechanistic frameworks (like physics-informed neural networks and grey-box modeling) to enable predictive simulations of chemical and biochemical