72 model-driven-development "Integreat Norwegian Centre for Knowledge driven Machine Learning" Postdoctoral positions at Duke University
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computational models and reproducible analytical pipelines. Validate automated behavioral measures against expert human coding standards. Develop approaches that support objective measurement of caregiver
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modeling, survival analysis, mediation analysis, trajectory modeling, and predictive modeling. Develop reproducible analytic workflows including data cleaning, cohort development, documentation, code
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the tumorigenicity of WT, D16, and p95 HER2 and using these models to test whether HER2 ICD- and p95 HER2-based vaccines generated by the laboratory prevent isoform-driven tumor formation Histological and molecular
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on the development of a calibrated agent-based HIV epidemic simulation representing populations in the U.S. South. The model will incorporate realistic network structures, behavioral dynamics, treatment uptake and
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the molecular and cellular mechanisms of vision and retinal disease. This position offers an exciting opportunity to contribute to innovative research focused on the development and maintenance of the light
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deep learning for CT image analysis and reconstruction Computational and digital-twin models for preclinical imaging Analysis of longitudinal and dynamic imaging data Development and validation
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to understanding the fundamental mechanisms that drive cancer development, treatment response, and therapeutic resistance. By combining cutting-edge molecular biology, functional genomics, and translational research
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access to state-of-the-art facilities. Join us in our mission to advance our understanding of alveolar development, homeostasis, regeneration, and pathology. Your valuable contributions will significantly
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, or presentations. Experience contributing to grant development and collaborative research projects. Desired Attributes The ideal candidate will be: Curious, innovative, and driven to advance epilepsy and sleep
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proteostasis, cytoskeletal dynamics, and ferroptotic cell death. This collaborative work combines biochemistry, chemical biology, cell signaling, live-cell imaging, and organotypic brain slice models to dissect