88 phd-mathematical-modelling-population-modelling Postdoctoral research jobs at University of Washington
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scientific papers, and contribute to the overall preparation of research for publication. To assist in the training of PhD and undergraduate students. Working Conditions: This position works in a laboratory
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to Rui Tang, PhD, Assistant Professor at ruit@wustl.edu . Cover letter expressing your interest and highlighting your relevant experience. Curriculum Vitae (CV) with a list of publications. Contact
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Position Summary Dr. Amargant-Riera’s research laboratory focuses on understanding the mechanisms that define oocyte quality. The lab uses mouse models and human samples to investigate
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, to define novel biomarkers, and to identify novel therapeutical targets. We have pioneered in the integration of genetics with omic data to identify proteomic signatures and develop novel predictive models
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disorders) populations. Our collaborative team is focusing on face-to-face interaction between children and their parents employing various methods to measure neural and behavioral responses during live
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PCR assays Coordinate and conduct clinical studies to validate the cell-free DNA assay, determine its diagnostic accuracy across different patient populations (including children), and compare
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of mutual interest such as, but not limited to, automatic machine learning model selection and automatically explaining machine learning classification / prediction results. The Luo lab is in UW Medicine’s
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, multimodal transportation systems, network modeling, etc. Duties will include conducting original research, disseminating research findings, supervising undergraduate research students, managing projects
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metropolitan area, with a dynamic, multicultural community of 3.7 million people and a range of ecosystems from mountains to ocean. The UW serves a diverse population of 80,000 students, faculty and staff
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, tumor immunology organotypic in-vitro models, genetically engineered animal models and human tissues from clinical trials. All these approaches are brought to bear on impactful questions in tumor