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Duke University, Electrical and Computer Engineering Position ID: Duke-Electrical and Computer Engineering-POSTDOC_YIRAN [#31802] Position Title: Position Type: Postdoctoral Position Location
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multiple affiliations. Be You. Duke School of Medicine’s interdisciplinary Duke Molecular Physiology Institute (DMPI), is seeking a highly motivated Postdoctoral Fellow with a PhD in computational biology
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. The investigator collaborates with interdisciplinary clinical teams to integrate these computational tools directly into hospital workflows. Routine duties include algorithm optimization and the evaluation of model
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the context of critical illness. This position focuses on computational modeling of host-response mechanisms using high-dimensional multi-omics datasets. The fellow develops novel computational pipelines
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addition to pursuing their own research agenda, we seek applicants with experience in survey design and computational methods, and working with complex large-scale data. Successful candidates will have completed a Ph.D
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within Imaging Services, including a clinical ladder program with various steps and opportunities across the health system. Required Qualifications at this Level Education: Graduate of an ARRT or NMTCB
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—induced by targeted drugs—can serve as a powerful therapeutic avenue in prostate cancer. Working under the mentorship of a Duke faculty leader, you will develop your independent research program, contribute
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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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, 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