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on within host mathematical and evolutionary modeling to understand HIV persistence and cure. At Fred Hutchinson Cancer Center, all employees are expected to demonstrate a commitment to our values
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cycling. Previous experience applying Bayesian inference, data assimilation, inverse modeling, and/or probabilistic machine learning to geoscientific or ecological models is highly desirable. Experience in
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the fundamental mechanisms shaping plant communities and their response to climate change. Qualifications: • PhD in Ecology or a related field • Strong quantitative background (e.g. ecological theory
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in this? You hold a PhD in chemical ecology or a closely related field. You have experience in research involving live insects and chemical analyses (e.g., GC-MS, LC-MS). You are skilled in designing
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this, we apply a combination of cutting-edge genomic analyses and laboratory experiments to interrogate multi-ethnic patient samples, laboratory cell lines and animal models. Ongoing and future projects
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plants. • Knowledge of 3D modelling. • Strong mathematical and analytical skills. • Excellent organizational and project management abilities to ensure timely delivery of outputs. • Excellent
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to geoscientific or ecological models is highly desirable. Experience in high performance an advantage. The candidate must have proof of excellence in research as demonstrated through publications in refereed
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applications in environmental health and ecology as well as working with motivating datasets to become familiar with the data structure, challenges and competing methods. This position requires a Phd degree in
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This position is a good fit for you if you recognise yourself in the following: You hold a PhD in one these fields: computer science, information science, industrial ecology, operational research, environmental
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samples, laboratory cell lines and animal models. Ongoing and future projects include (i) genomic and functional characterization of molecular drivers of women’s cancers, (ii) biology and therapy