86 developer-"https:"-"https:"-"https:"-"UCL"-"UCL" Fellowship positions at Zintellect
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developing and applying process-based simulation models, especially dynamic food web models and bioenergetic models. Experience in multi-disciplinary teams, including other natural sciences, social scientists
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offering a graduate research fellowship at the Combat Capabilities Development Command – Chemical Biological Center (DEVCOM-CBC). As a research fellow, you will join a community of scientists to support our
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on-going applied research and development projects in the areas of Environmental Health, Engineering, Biological Sciences, Public Health, Occupational and Environmental Health, Industrial Hygiene
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asphalt binders in new pavements. Under the guidance of a mentor, the participant will participate in the development and optimization of chemical processes to improve the performance of biobased additive
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businesses to develop new technologies to enhance the nutritional and functional qualities of plant-derived foods. Their research also values ingredients from novel food sources and agricultural by-products
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pursues disruptive qubit research, innovative workforce development programs, and deep, collaborative partnerships to tackle some of the hardest open problems in quantum information science and technology
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and weaknesses for end-users. Help develop new or improve existing soil moisture estimates using NISAR and other datasets utilizing artificial intelligence (AI) and machine learning. The outcome from
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agricultural pest systems is highly desirable. Learning Objectives: The overall research goal of the group is to develop new pest management strategies that can augment and enhance current approaches. As such
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supply. The fellow's research supports the mission and goals of ARS National Program 108, Food Safety (100%). The candidate will be a part of development of sustainable technologies that solve
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biodefense, biosecurity, or international trade implications. They will collaborate with ARS scientists to develop innovative approaches to describe, identify, and detect microbes found in crop and/or weed