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or equivalent and a PhD (or close to completion) in computer science, math or comparable, or an applied/life science (e. g. engineering, biology, medicine) with a focus on data analysis and/or machine learning
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hydraulic modeling. 80% research - The project focuses on developing theoretical models using optimization to improve understanding of plant stomatal regulation at the leaf, plant, and ecosystem scales. 20
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disabilities. Minimum Qualifications Doctoral degree (PhD, MD, DDS, PharmD, etc.) in a relevant field Preferred Qualifications Doctoral degree in climate and/or health related field Physical Demands Salary Range
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will work with data collected from the field to the spatial scale, and investigate spatial optimization approaches to improve the model parameterization at the spatial scale. We expect that you will be
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will work with data collected from the field to the spatial scale, and investigate spatial optimization approaches to improve the model parameterization at the spatial scale. We expect that you will be
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Position Summary This position will primarily support the implementation of a newly funded National Institute of Mental Health R01 grant focused on optimizing a digital chatbot intervention for
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We invite applications for a Postdoctoral Appointee to contribute to a growing research program in process systems modeling and optimization for clean energy, critical materials, and advanced
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machine learning—for chemical and biological applications. You will design and implement models ranging from molecular to process scales, develop model-predictive control and optimization strategies, run
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. The postdoctoral fellow will lead a project focused on developing optimized strategies for observing, processing, and archiving the datasets from current and future large astronomical facilities, with emphasis
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studies: Trauma Intervention to Optimize PrEP Among Women Who Inject Drugs (TIARAS) is a randomized controlled trial is to test the effectiveness of a trauma intervention designed to reduce HIV acquisition