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state-of-the-art verification techniques and tools for scientific software. The project is part of a program, sponsored by the U.S. Department of Energy and the U.S. National Science Foundation, named
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proficiency in at least one statistical software (e.g., R, Stata, SAS, Mplus) and desire and ability to learn additional software as needed (note: Dr. Kuiper regularly uses R, Stata, and Mplus simultaneously
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Computer Science or related fields Experience in power system modeling, optimization, and control Experience in at least one of the power system software tools including OpenDSS, PSCAD, PSS/E Experience in at least
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the energy transition Experience and competency in quantitative analysis, including applied econometrics Experience in applied theoretical modeling a plus Proficient at statistical software, e.g., STATA
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interdisciplinary and collaborative team of engineers, analysts, and software developers. GAC works to develop and apply state-of-the-art energy system modeling techniques, software, and simulations for breakthrough
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: -Excellent verbal and written communication skills. -Ability to analyze data and write reports. -Ability to utilize a computer and applicable software. -Ability to multi task and work cooperatively with others
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software for genetic analysis of polyploid plant species, and ability to work with databases and to handle large data sets. Experience in phylogenetic analysis, marker trait association studies and genomic
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with survey design methodologies and software. Strong quantitative and mixed‑methods skills. Excellent written and oral communication skills. Preferred Qualifications: Experience with ecosystem services
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, original forms of identification for employment verification via the Federal I-9 employment verification process. Click here for a list of acceptable documents. Important: To apply you must create a profile
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. Collaborate with a multidisciplinary team of engineers, computer scientists, and data scientists to put research insights into open-source software products. Publish research findings in leading academic