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program might include, for example, (1) building methods to improve undergraduate learning in the Plant Sciences; (2) developing novel assessment tools; (3) studying how student metacognition affects
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systems based on an analysis of their current architecture and operational data. Machine learning and neural network architectures, including convolutional, recurrent and transformer networks. MLOps and
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geothermal resources, reservoir modeling, techno-economic analysis and machine learning implementation, and other emerging geothermal energy-related topics. The selectee will be expected to develop funding and
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genuine candidates remains challenging. This project will leverage state-of-the-art machine learning and bioinformatics to address key challenges in identifying signaling peptide candidates, predicting
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excellent knowledge of educational technology/learning sciences, XR technologies, and AI, as well as deep knowledge of advanced data analysis methods. The researcher will contribute to multiple cutting-edge
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psychometrics, big data/machine learning, or a related approach). Demonstrated evidence of expertise in SBHE-related research methods (e.g., experimental or quasi-experimental designs, intervention efficacy
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bioinformatics area) position is open at Duke University School of Medicine in the lab of Dr. Yi Zhang starting Jan 2024 or later. The ideal candidate will develop novel statistical and machine learning methods