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senior research position to work on projects related to computational analysis of mass spectrometric datasets. A major focus will be on the application of AI/machine learning models and other computational
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doctoral degree in Computer Science or Biomedical Informatics or a closely related quantitative field. The successful candidate demonstrates documented expertise in machine learning and distributed
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discipline expertise and computational areas, such as data science, artificial intelligence (AI), machine learning (ML), generative AI and other technology innovations. Key details of this position include
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data analysis is required. The lab mostly uses R for data analyses; knowledge of R is not required, and the postdoctoral scholar will have the opportunity for mentorship and learning. To Apply: Motivated
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skills in qualitative research methodology, including experience conducting interviews, focus groups, and thematic analysis Possess technical skills in AI/machine learning, software development
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work is studying how undergraduate STEM courses can be tailored to meet the needs of all learners. Current projects involve studying STEM instructor perceptions of student-centered learning as
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one or more of: computational modeling of social learning, norms, or moral cognition; cultural evolution and gene-culture coevolution; evolutionary game theory and the evolution of cooperation
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their surfaces. Machine learning methods are used to close the complexity gap. Currently, the group consists of three full professors, one associate professor, 6 postdocs and about 15 PhD and 7 master
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humanities disciplines. Familiarity with contemporary AI systems (e.g., machine learning, generative models) at a conceptual or applied level. Experience with qualitative or mixed research methods (e.g
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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