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mathematics and learn more about modeling of atmospheric or oceanic flows, or the motion of charged fluids such as plasmas? We are looking for a Doctoral student to become part of Klas Modin's group
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leverage large-scale AI models to: integrate heterogeneous EO data sources, such as satellite, aerial and in-situ data, across spatial and temporal scales; enable zero-shot or few-shot learning for rapid
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Your Job: In this position, you will be an active member of the SDL “Fluids & Solids Engineering” and will collaborate strongly with the SDL “Applied Machine Learning”. You will have the following
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Freedom found on-line at https://www.usg.edu/policymanual/section6/C2653 . The University of North Georgia, a regional multi-campus institution and premier senior military college, provides a culture of
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automation, and deployment frameworks. Familiarity with machine-learning integration, including packaging models for production, reproducible workflows, and environment management. Strong programming skills in
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. Technical skills: Proficient in using E-views and Stata for econometric modeling. Advanced expertise in business intelligence, data analysis, data science, and machine learning tools. Capable of developing
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biomarker data. Develop predictive models and algorithms to identify risk factors, disease markers, and potential therapeutic targets for Alzheimer’s disease. Implement machine learning models to improve
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organisms respond to hypoxic stress and nervous system function using the model organism C. elegans. The individual will report directly to the laboratory Principle Investigator (PI). Position Status Full
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computational resources to ensure the efficiency of analysis, modeling, and machine learning tasks. The researcher also contributes to defining policies that ensure security, service continuity, and scalability
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that can be run. Emulating expensive processes could allow more data to be generated from better models, at lower cost. The central science question is: how can machine learning and evolutionary computation