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Postdoctoral Associate to begin July 1, 2026. The one-year term position is renewable for an additional year based on performance and is part of Cornell’s Active Learning Initiative . This initiative supports
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, 2026. The one-year term position is renewable for an additional year based on performance and is part of Cornell’s Active Learning Initiative . This initiative supports departments in integrating active
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next generation of scientists and build a workforce equipped with expertise in integrating advances in biomedical engineering, technology, and Artificial Intelligence (AI) and Machine Learning (ML
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at the intersection of educational data science, AI in education, and the learning sciences, with additional advisory support from faculty and researchers across learning sciences, computer science, machine learning
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Associate as part of Cornell’s Active Learning Initiative (https://teaching.cornell.edu/active-learning-initiative-0) for the AYs 2026 – 2028. We invite applications from candidates with a specialization in
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comparative genomics, chromatin architecture, gene expression, protein abundance, and metabolite profiling—combined with computational biology, machine learning, and advanced statistical methods. Supported by
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workforce equipped with expertise in integrating advances in biomedical engineering, technology, and Artificial Intelligence (AI) and Machine Learning (ML) methods to tackle complex biomedical challenges in
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crane. The successful candidate will build reproducible machine learning pipelines, integrate detections into spatial ecological models, and generate conservation-relevant outputs for regional partners
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researchers across learning sciences, computer science, machine learning, and education research. Research Role Research themes for the NTO Postdoctoral Associate include, but are not limited to: Developing
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of active learning pedagogy that strengthens ‘systems-thinking’ throughout the cross-college Environment & Sustainability (E&S) major. This is a full-time position, based at the Ithaca campus. We expect