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), including sample preparation, data collection, data processing, model building, and refinement Experience with in vitro biochemical and biophysical assays Record of scientific productivity demonstrated
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laboratories, utilizing real-world utility data and models to address practical and impactful challenges in modern power systems. The selected candidate will contribute to the development of innovative solutions
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of the appointment. Demonstrated proficiency in data analysis, statistical modeling, and data visualization using R, Python, or comparable analytical software. Evidence of effective scientific communication through
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continued funding availability. Required Minimum: PhD degree in Civil Engineering Preferred Qualifications: Demonstrated expertise in water resources and ecohydrological modeling. Demonstrated research
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the instrumentation, developing the data analysis methods, and applying the methods to study model biomolecules and biomass systems. This research is part of the laboratory’s work for an Office of Science, Biological
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population genomic analyses of crop species Experience managing and analyzing large-scale biological datasets Experience using SLURM-based high-performance computing systems Demonstrated proficiency in R
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, modifying, and functionalizing porous materials (especially zeolites, oxide, and carbon-based materials) and single-site catalysts. Demonstrated extensive experience characterizing catalytic materials
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Researcher will develop machine learning (ML)-based methods for reaction dynamics simulations in both gas-phase and condensed-phase systems. The primary focus of this position is the development and
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Qualifications: Experience in proteomic data analysis and laboratory bench work related to proteomics. Experience operating image-based flow cytometry platforms and analyzing resulting datasets. Experience
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, interdisciplinary research environment. Key Responsibilities Develop and advance non-thermal plasma-based technologies for: Nitrogen fixation Valorization of renewable feedstocks Conversion of waste streams