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Field
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The School of Materials Science and Engineering (MSE) provides a vibrant and nurturing environment for staff and students to carry out inter-disciplinary research in key areas such as Computational
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Computer Science, Mathematics, Physics, Applied Economics, or a related quantitative field. Skills and Knowledge: Knowledge of scientific computing, data assimilation, and machine learning frameworks. Proficiency in
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well as their relationships with China in the East and Europe in the West. The research project can be situated in any discipline or interdisciplinary position and can address any aspect of the movement of materials, knowledge
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Requirements: Have relevant competence in the areas of material science and chemical synthesis Have a degree in materials science/ chemistry. Possessing a Master’s or PhD degree will be advantageous with prior
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cost savings in aerospace manufacturing. We aim to develop a life cycle-informed design approach that enables rapid assessment of the cost and environmental impacts of recyclable and recycled materials
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University of North Carolina at Charlotte | Charlotte, North Carolina | United States | about 4 hours ago
Position Information General Information Position Number POST40 Working Title Postdoctoral Fellow - Computer Science Division Academic Affairs Department Coll of Computing&Informatics (Col) Work
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Qualifications: PhD in immunology, cancer immunology, autoimmune diseases, human genetics, molecular biology or biochemistry Experience in autoimmune diseases, preclinical animal disease models, multi-color flow
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motivated candidates for postdoctoral fellow positions within the Bureau’s hydrology research group. These fellows will be key members of an expanding research program focused on assessing Texas water
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operations, business affairs, as well as learner professional educational needs. Oversee, delegate, and assist with coordinating the development of program materials including educational and training
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Biotechnology and Bioprocesses, Membrane Technology, Chemicals and Materials, Resource Recovery, and Modeling & Artificial Intelligence. By harnessing its cross-cutting, interdisciplinary, and transformative