SALT LAKE CITY, UT1 day ago
Rather than cataloging datasets cited by papers, this effort focuses on identifying and organizing information about: AI models mentioned or used in publications model families, versions, checkpoints, and architectures tasks and scientific domains in which models are applied evidence of reuse, benchmarking, fine-tuning, and comparison links among papers, models, repositories, benchmarks, and supporting resources search, ranking, and visualization interfaces for model-centric scholarly explorationThis work sits at the intersection of AI/NLP, scholarly knowledge extraction, software engineering, data infrastructure, and human-centered discovery systems. This role offers exceptional opportunities to: contribute to high-impact interdisciplinary research publish and present work in relevant venues collaborate with experts in AI, data systems, and scientific computing gain hands-on experience with production-grade research software and infrastructure mentor students and junior developers shape the future of AI-ready scholarly discovery platformsWork EnvironmentYou will contribute to cutting-edge computational methods for AI-ready model discovery, research knowledge extraction, and scientific search systems.