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Field
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of the microbial ecology results in mineralized environment in the petrology and thermodynamic modeling components of the project. This project involves 6 (teachers)-researchers and research engineers from
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humanities disciplines. Familiarity with contemporary AI systems (e.g., machine learning, generative models) at a conceptual or applied level. Experience with qualitative or mixed research methods (e.g
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for the analyses will be the intervention plans of multi-stakeholder platforms (Ethiopia) and expected behaviors of agripreneurs and farmers (Kenya) using agent-based models; Assess the potential for co-developed
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pipelines to resolve synapse nanostructure in rodent brain tissue. is motivated to experimentally and conceptually integrate molecular and circuit level neuroscience. has good communication skills and a
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Scholar to join a Sloan Foundation–funded research project led by Prof. Eamon Duede . The project investigates how the rapid emergence of artificial intelligence (particularly large language models) is
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advanced epidemiologic and biostatistical methods, including causal inference, survival and longitudinal modeling, and approaches for integrating multi-level and high-dimensional data. There will be
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for learning, problem-solving, and assessment. How AI technologies influence cognitive and metacognitive processes, such as reasoning, conceptual understanding, and self-regulation in learning. Institutional
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reasoning, conceptual understanding, and self-regulation in learning. Institutional responses, governance models, and ethical frameworks shaping the integration of AI in higher education. We especially
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involved in other collaborative research projects between Coley’s Conceptual Organization, Reasoning, and Education Laboratory (CORE Lab) and Helmuth’s Marine Ecological Forecasting, Ecophysiology, and
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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
vulnerabilities. The Postdoctoral Appointee will be responsible for the conceptual framework, design, and implementation of these models, ensuring scalability on the DOE’s leadership computing facilities. Position