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moves. Success will be measured by having published or contributed to papers in top venues (e.g., Nature Science of Learning, Computers and Education, ACM Learning at Scale, Educational Data Mining) and
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, Japanese history (esp. early modern), historical geography, GIS, programming (esp. Python) and computer science, statistics and data science, text mining, natural language processing, demography, economics
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analysis involving gathering and combining data from a range of different existing databases. The candidate should have excellent written and spoken English proficiency. Furthermore, the ideal candidate will
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of agricultural in dry lands and marginal environments, animal value chain, water and energy sustainability, biorefinery and bioenergy, cultivation and conversion of micro and macroalgae, and geology and mining
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development, translational medicine, bioinformatics&data mining, and AI-enabled biomedical engineering. As a faculty member at SUSTech, you will have the opportunity to shape the future of your career while
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Experience with machine learning, data mining and data assimilation is a plus Knowledge of git, docker, kubernetes, and/or metadata is a plus Ability to work within a team Excellent interpersonal and
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chamber development, and (3) field studies in mining environments. Perform advanced sample analysis, validate measurements, and document findings. Process and analyze research data to generate meaningful
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. For more information about working at the University of Arizona and relocations services, please click here . Duties & Responsibilities Conduct independent research on (1) polymer self-assembly and
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drainage, cultivation, and mining. As these areas constitute major sources of carbon dioxide emissions, accurate mapping is crucial for their effective restoration and management. Peatlands are highly
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drainage, cultivation, and mining. As these areas constitute major sources of carbon dioxide emissions, accurate mapping is crucial for their effective restoration and management. Peatlands are highly