11 linked-data "https:" "https:" "https:" "https:" "https:" "https:" "https:" "IDAEA CSIC" Fellowship research jobs at The University of Alabama
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to characterize aquifer recharge, preferential flow pathways, and contaminant transport; supports groundwater modeling and decision-support tools; and integrates geophysical and environmental data to evaluate
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Pay Grade/Pay Range: Minimum: $54,000 - Midpoint: $67,500 (Salaried E8) Department/Organization: 214251 - Electrical and Computer Eng Normal Work Schedule: Monday - Friday 8:00am to 5:00pm Job
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natural history. Fellows will work under the supervision of one or more Biological Sciences faculty conducting relevant research (https://bsc.ua.edu/directory/). Required Minimum Qualifications: Doctorate
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the DREAM lab (https://sites.ua.edu/dreamlab/). Skills and Knowledge: Knowledge/expertise in molecular pharmacology and experimental therapeutics. Data analysis experience. Strong written and verbal
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natural history. Fellows will work under the supervision of one or more Biological Sciences faculty conducting relevant research (https://bsc.ua.edu/directory/). Applications will be evaluated by
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sensors. Ability to collect, process, and analyze complex environmental datasets. Proficiency with scientific programming and data analysis software. Ability to prepare technical reports, manuscripts, and
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with community-based research or implementation science. Training in advanced statistical methods, qualitative methodologies, or mixed methods. Experience with electronic health records (EHR) data, large
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, or chemistry. Preferred Qualifications: Strong analytical skills are beneficial, including but not limited to XRD, IR, SEM-EDS, TGA, DTA, and electrochemical techniques. Experience with data visualization and
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candidates for a Postdoctoral position. This position is available to individuals with research interests and expertise in modeling and data analyses of hydrologic processes. Initial appointments are for one
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Investigation Statement: Prior to hiring, the final candidate(s) must successfully pass a pre-employment background investigation and information obtained from social media and other internet sources. A prior