28 model-driven-development "Integreat Norwegian Centre for Knowledge driven Machine Learning" Postdoctoral positions at Iowa State University
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processes. Successful candidates will contribute to developing innovative solutions for nitrogen fixation, renewable resource valorization, and waste-to-value conversion while working in a collaborative
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. Successful candidates will contribute to developing innovative solutions for nitrogen fixation, renewable resource valorization, and waste-to-value conversion while working in a collaborative
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-on experimental development of metallothermic routes for producing rare earth metals from rare earth compounds, including oxides, chlorides, and fluorides. This work builds on the “Ames Process” for rare earth
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, and trusted to deliver innovative, science-driven solutions to the most pressing challenges in animal health and food production. We advance our vision by empowering current and future veterinarians
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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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science, and soil science. The successful candidate will contribute to innovative research on soil-plant interactions while developing new skills in a collaborative and supportive research environment. Key
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datasets using advanced data science techniques and communicate findings through technical reports and presentations. The position will also contribute to the development and publication of scientific
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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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University seeks a Postdoctoral Research Associate to join the research group of Professor Aaron Rossini. The successful candidate will conduct experimental research focused on the development and application
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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