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and structure modeling for protein, RNA, or small molecule. Apply computational techniques, data analysis, and visualization methods for ongoing studies. Train and validate large deep learning models
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are the following key elements: To extend the frontiers of knowledge through research and other scholarly endeavors. To build and enhance student competencies for successful careers. To apply research-based
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at the discretion of the School Director: Fall: ARE 4243C, Principles of Teaching Art ARE 6386, Teaching Art in Higher Ed ARE 6746, Methods of Research Spring: ARE 2045, Intro to Art Ed ARE 4934C, Student Teaching
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ideally August 18, 2025. The project uses interdisciplinary methods from social network science, language modeling, and cognitive science. In this longitudinal project we will follow learners of Spanish who
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to work at the forefront of environmental remote sensing, leveraging unique datasets and advanced computational methods to address critical questions in land change science and fire ecology. The position is
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. The successful candidate will contribute to the Department of History’s intellectual growth and innovative teaching methods, and to the development and growth of undergraduate experiential learning opportunities
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, medical image processing, metabolomics data analysis, survival analysis, causal inference, statistical methods of health surveys, high dimensional inference, longitudinal data analysis, and clinical trials
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research university, and the desire to work collegially within a goal-oriented fundraising organization. Knowledge of fundraising principles, methods, and standards. Expertise in developing solicitation
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complex analyses. Appropriately apply quantitative and qualitative methods to interpret data trends, correlations, and patterns. Produce actionable insights, draw meaningful conclusions and develop
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at the discretion of the School Director: Fall: ARE 4243C, Principles of Teaching Art ARE 6386, Teaching Art in Higher Ed ARE 6746, Methods of Research Spring: ARE 2045, Intro to Art Ed ARE 4934C, Student Teaching