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join a highly collaborative, interdisciplinary research environment focused on developing and applying cutting-edge machine learning and deep learning methods to abdominal imaging. Working alongside
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Partner with experts in child development, psychiatry, engineering, computer vision, and machine learning. Contribute to study design, scientific strategy, and interdisciplinary research planning. Work
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and application of advanced computed tomography methods, with a focus on photon-counting CT, quantitative image analysis, and machine learning. The position will involve work across several NIH-funded
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Bayesian inference, likelihood-free inference, uncertainty quantification, identifiability analysis, or scientific machine learning. Strong programming skills (Python, Julia, Matlab, C++, or similar). Strong
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discoveries made in the laboratory with meaningful improvements in patient care. You will be part of a research environment that values curiosity, creativity, scientific rigor, and continuous learning while
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Be You. At Duke, we celebrate individuality and the unique perspectives that each member of our community brings. As the Machine Learning Research Data Analyst, Ophthalmic Imaging, you'll play a
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Academic credentials: PhD in ecology, biology, statistics, computer science or engineering, or oceanography with a strong quantitative analysis background, particularly in species distribution modeling
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, learning, well-being, social experiences, and decision-making. HARP is developing a longitudinal multimodal research resource to study human-AI interaction and its impacts using student-informed, privacy
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research in engineering and science related to critical minerals. This position will contribute to building interdisciplinary excellence and research pathways in critical minerals research at Duke University
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development of machine learning tools and their applications to medical imaging. Key Responsibilities: The Post Doctoral Associate will apply their technical skills toward the development, implementation, and