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analysis and machine learning methods applied to protein structure determination using single-particle cryo-electron tomography (ET). The candidate will contribute to the design, development, and
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, Duke University Biology Department to study how archaeal microbial communities respond to stress in hypersaline environments. A PhD in computational and/or experimental biology is required in fields
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collaboration between Dr. Warren Grill and Dr. Angel Peterchev at Duke University and Dr. Axel Thielscher at the Danish Research Center for Magnetic Resonance and Technical University of Denmark. This work is
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for Magnetic Resonance and Technical University of Denmark. This work is part of a long-standing research program at Duke for rigorous computational modeling and experimental characterization of both invasive
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the Interpretable Machine Learning Lab (https://users.cs.duke.edu/~cynthia/home.html ) for a scientific developer to work in collaboration with other researchers on machine learning tools that help humans make better
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. Qualifications: Qualifications include a PhD or equivalent in environmental health, epidemiology, biostatistics, or a closely related discipline. The successful candidate should be highly organized and have
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to mentor students, teach/train other researchers in LCA tools, and develop independent research projects as desired. The successful applicant will possess a PhD in chemical engineering, chemistry
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for this position will be a highly motivated individual with experience in deep learning and medical imaging and a PhD degree in computer science, electrical and computer engineering, biomedical engineering
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applications of deep learning, medical imaging, and biomarker integration. This full-time, one-year position offers a unique opportunity to engage in impactful research at the intersection of AI, connectomics
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scientific machine learning in solving problems in solid mechanics and dynamic wave propagation, in particular: (i) developing domain decomposition methods, (ii) damage models, (iii) nonlinear mechanics. 2