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program and complete the degree prior to the appointment start date. The ideal candidate would have some, but not necessarily all, of the following: PhD. in Materials Science, Chemical Engineering
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wildland-urban interfaces— across a wide range of climate conditions. Using machine learning methods, we will optimize the weightings of each contributing factor and identify the key drivers of wildfire risk
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. Qualifications The qualified candidate should hold or be currently pursuing a master's degree or PhD in Mechanical Engineering, Biomedical Engineering, or a related discipline. Postgraduates must have earned
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PhD in a relevant field such as structural mechanics, heat transfer, numerical optimization, topology optimization, or lattice design. The postdoctoral scholar will be responsible for vigorously
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production using state-of-the-art data science methods, leading to improved research in forestry and economics. Additionally, the fellow will be invited to participate in the broader research goals using
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surveys and other anecdotal collection methods Combine empirical evidence gathered from web/social media analytics Study data associated with content Collaborate with other team members to create multimedia
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including measurements of electrical conductivity, enzyme kinetics, pH, unconfined compressive strength, etc. Share the findings of the research via a formal technical presentation Where will I be located
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activities including measurements of electrical conductivity, enzyme kinetics, pH, unconfined compressive strength, etc. Share the findings of the research via a formal technical presentation Where will I be
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conditions they are likely to be useful. For this reason, we have assembled a research team to explore new methods and new data that will improve foundational fuel structure and flammability information
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one another; and delivering world-class science, technology and land management. Research Project: The fellow will contribute their PhD-level social science research skills to understand how project