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, evidence-based practice, and interdisciplinary collaboration to lead the future of nursing. Our nursing program stands as a leader in healthcare education, earning #1 in the nation for Best Bachelor
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Description: Apply Position Description The Duke Quantum Center is seeking a Postdoctoral Researcher to work on ion trap quantum computer and quantum network projects, supporting/advancing research in quantum
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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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primary benefit. This postdoctoral appointment is part of the Duke University Aging Center’s NIA-funded T32 Postdoctoral Research Training Program. This multidisciplinary program is focused on developing
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, and analyzing current or future quantum simulations at the intersection of subatomic physics and quantum information science. The successful candidate will also lead peer-reviewed publications and
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, evidence-based practice, and interdisciplinary collaboration to lead the future of nursing. Our nursing program stands as a leader in healthcare education, earning #1 in the nation for Best Bachelor
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international and regional leadership in biostatistics, genomics, biomedical informatics, artificial intelligence and health data science. We are recruiting a creative, rigorous Postdoctoral Research Scientist
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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 university and with industry to translate discoveries into clinical proof of concept studies. Working with a team led by Drs. H. Kim Lyerly, Zachary Hartman and Josh Snyder, this program spans basic discovery