111 fully-funded-phd-program-computer-science Postdoctoral positions at University of Washington in United States
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Position Overview School / Campus / College: College of the Environment Organization: Environmental and Forest Sciences Title: Postdoctoral Scholar: Sustainable Polymers Position Details Position
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, research and evaluation, and program development and policy efforts across the SPIRIT Center. Psychodiagnostic assessments and research will be primarily conducted on the campus of Harborview Medical Center
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Description A postdoctoral fellowship position is available in the Elbert Laboratory in the Department of Neurology at University of Washington in Seattle, Washington, USA. The project is funded for two years
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their way. Qualifications PhD (or other foreign equivalent) at the time of hire in Microbiology, Cell Biology, Biochemistry, Bioengineering/Biomedical Engineering, Biophysics, or related fields, and 1 or more
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criteria apply. For more information, please visit the University of Washington Labor Relations website . Qualifications PhD in ecology, forestry, environmental science, or a closely related field by
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under supervision, with the goal of establishing an independent research program and career path. The postdoc will be based at the University of Washington – Seattle Campus. The preferred start date is
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NW). This is a full-time position with a 12-month service period (July 1-June 30), with the possibility for yearly renewal dependent upon performance and continued funding. The base salary range
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Qualifications: PhD or foreign equivalent in Biology, Molecular Genetics, Fisheries Science, Statistics or related disciplines Experience in basic laboratory techniques Thorough knowledge of population genetics
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DNA in easily accessible urine samples. Our recent work is getting significant attention from clinical researchers and technology developers, and we aim to advance our collaborations and develop
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industrial engineering, systems engineering, computer science, electrical engineering, or a related field. · Strong background in machine learning or data analytics and hands-on experience handling big