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, United States of America [map ] Subject Areas: Mathematics / applied mathmetics , Mathematical Sciences , Partial Differential Equations , Statistics Computer Science Machine Learning Appl Deadline: none (posted 2025/08
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regional leadership in biostatistics, genomics, biomedical informatics, artificial intelligence and health data science. The Postdoctoral Associate will conduct research in statistical machine learning and
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). Duke is committed to encouraging and sustaining work and learning environments that are free from harassment and prohibited discrimination. Duke prohibits discrimination and harassment in
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/ ) research examines learning and conceptual change in young children with a focus on social learning and social cognition. Research topics include: mechanisms of causal learning, the developmental origins
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to climate, environment, or sustainability challenges. • Required skills: o Strong quantitative background, with expertise in one or more of the following: statistical modeling, machine learning, remote
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) Experimental investigation and computational model simulation of laser-induced bubble dynamics and material damage assessment 3) Developing AI and machine learning models for robot-assisted laser surgery and
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the global health scenario and domestically for dissemination, and plenty of opportunities for career advancement. •Learn background/research methods of studies for which analysis is conducted with limited
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renewal. The Fellow will be expected to be in residence, to conduct research in Duke's library and archival collections, to participate actively in the intellectual life of the university, to teach up to 2
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-mentored research, teaching innovation, and public engagement, providing Fellows with resources and networks to launch impactful careers. To learn more about the SCALES Postdoctoral Fellowship Program, visit
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related field • Strong quantitative background (e.g. ecological theory and mathematical modeling, hierarchical statistical modeling, machine learning, remote sensing, geospatial statistics) • Demonstrated