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of state voting legislation for the Voting Laws Roundup. This work includes developing computational tools (e.g., using large language models, machine learning for text analysis and classification, etc
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Max Planck Institute for Multidisciplinary Sciences, Göttingen | Gottingen, Niedersachsen | Germany | 13 days ago
40 research groups and some 1,000 employees from over 50 nations, it is the largest institute of the Max Planck Society. The Department of Theoretical and Computational Biophysics headed by (Prof. Dr
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of Canada interested in pursuing a post-doctoral research project related to access to justice for official language minority communities in Canada. Researchers may come from a wide variety of fields
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 2 days ago
diversity and brings together expertise in software engineering, big data, clinical informatics, and medicine. Key Responsibilities Collaborate with researchers to design, develop, and refine large language
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scientific journals and conferences Your Profile: A doctoral degree in Physics, Materials Science, Computer Science, Data Science, or related fields Proven experience with large language models (LLMs), natural
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conduct a dissertation according to the standards of the Faculty of Social Sciences at UiO . The candidate will be part of the PhD education and program at TIK and the Faculty and will be supported and
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curious to deliver work that matters, your journey starts here! The Language Technologies Institute (LTI) at Carnegie Mellon University is a world-renowned research and education hub at the forefront
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computer programming in R and Python *Formal training or experience applying quantitative and spatial methods to human-environment questions *Excellent academic writing and communication skills in English
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-doctoral associate for an NSF-funded project on the social, environmental and linguistic factors that affect human wayfinding. Working with the PI and co-PIs in computer science, psychology, applied math and
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challenging environments, where signals are extremely noisy and distorted, and include severe linguistic variations, particularly when data and computational resources are scarce. This will be tackled using a