26 parallel-and-distributed-computing-phd Postdoctoral positions at The University of Arizona
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Sign In Create Profile Postdoctoral Research Associate I, Information Science Tucson, AZ, United States | req25315 Apply Now Share Save Job Posted on: 3/3/2026 Back to Search Postdoctoral Research
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productivity while reducing external inputs. In parallel, the lab is expanding efforts to understand microbiome-associated phenotypes that contribute to drought tolerance and soil water retention. This includes
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). By developing improved understanding of recharge mechanisms, distribution, and susceptibility across the state, the project can identify safe locations for enhanced recharge activities and support
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technology, combining knockout and knock-in mouse models. Ideal candidates will have a MD and/or PhD in biochemistry, physiology, and nutrition. The position is part of a well-funded research program and will
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multidisciplinary teams and communicate technical results effectively. Strong programming skills in Python and/or MATLAB, with experience in scientific computing and simulation. Ability to design and analyze data
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imaging analyses using portable XRF or micro-XRF, to assess metal accumulation and spatial distribution in plant tissues. Carry out herbarium-based research and field sampling to identify and document metal
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research goals. Data Analysis, Interpretation, and Dissemination Analyze complex biological datasets using appropriate statistical and computational tools. Prepare figures, manuscripts, and abstracts
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& Responsibilities Conduct independent experiments and computational analysis, evaluate the data, and keep appropriate records of all research activities. Read the literature, participate in scientific discussions
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tabular, oral, written, and/or graphic formats. Minimum Qualifications PhD in Biology Sciences or relevant field of study. Preferred Qualifications Experience with flow cytometry, cell sorting, cell culture
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scientific research manuscripts. Minimum Qualifications PhD in the field of earth or planetary science Preferred Qualifications Proficiency with geophysical data analysis and modeling Demonstrated expertise in