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Field
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mixed methods, including interviews, participant observations, document studies, quantitative approaches and social interventions. The candidate must be familiar with some of these approaches. • Good oral
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metapopulation and/or individual based models Knowledge of Bayesian methods, including Approximate Bayesian Computation Experience with big data analysis and HPC environments Knowledge of additional programming
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computer skills Physical Demands Must be able to sit for extended periods of time and work in standard office environment Must be able to occasionally lift 20 pounds Must be able to work occasional weekends
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technology. Moreover, the close connection with the clinical environment allows for translation of novel methods to our cancer clinics in Canada (Vancouver, Victoria, and Kelowna) and beyond. RESPONSIBILITIES
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(LAFOV) PET/CT scanner, and aims to push the limits of modern technology. Moreover, the close connection with the clinical environment allows for translation of novel methods to our cancer clinics in
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acquisition and data analysis methods for users i) Troubleshoot equipment failures, procure repair parts, implement repairs, supervise field service, and test equipment for proper function after repairs j
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skills relevant to maintenance, repair, and modification of scientific instruments. Qualifications Experience with biological experimental design and implementation. Computer skills for instrument
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; assist with manuscript and grant writing; develop a K award, educate collaborators and lab members on methods used in analyses; supervise students rotating through the lab; stay abreast of new analytic
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appropriate conditions, it provides a confidence set (credibility set if prediction is Bayesian) for a multivariate estimate with statistical coverage guarantees. This PhD project aims to develop new CP methods
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teaching Experience with water infrastructure modelling with a focus on computational methods A strong link to the topic interdependence and cascading effects in Urban infrastructure Systems. A strong