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the remotely sensed LST to compute the spatial statistics, run the HydroBlocks model over the Contiguous United States, and evaluate model deficiencies and model improvements to improve the modeling of spatial
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. The Postdoctoral Associate will apply his/her technical skills toward development and implementation of machine learning, computer vision, and other algorithms for analysis of medical images and prognostication as
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Gastroenterology Research Training Program Postdoctoral Fellowship The Duke Division of Gastroenterology is seeking applicants for a two-year post-doctoral fellowship within the Duke Gastroenterology Research
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to precisely shift microbiomes to desired metabolic states. Our research combines multiplexed measurements of single cells, populations and ecosystems with concepts from nonlinear dynamical systems, control
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may include teaching responsibilities. The appointment is generally preparatory for a full time academic or research career. The appointment is not part of a clinical training program, unless research
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responsibilities. The appointment is generally preparatory for a full-time academic or research career. The appointment is not part of a clinical training program unless research training under the supervision of a
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Assessment Models (IAMs) such as GCAM or PAGE. The candidate must have a PhD degree in a related field, be fluent in computer programming, preferably python, and will ideally have experience in working with
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academic or research career. The appointment is not part of a clinical research training program, unless research training under the supervision of a senior mentor is a primary purpose of the appointment
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surface water dynamics using satellite and field data. This research may also include working with NASA’s new Surface Water Ocean Topography (SWOT) satellite, as well as the opportunity to conduct fieldwork
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independent research activities under the guidance of a faculty mentor in preparation for a full time academic or research career. Conduct research on computational modeling of cortical neuron activation by