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cancer development, progression, and metastasis. The successful candidate will combine advanced cell and tissue culture methods with bioengineered model systems, quantitative microscopy, and molecular
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novel infant gut models and apply it to investigate microbiota–immune-pathogen interactions, generating knowledge that can support future interventions to improve infant health. We welcome applications
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initial problem specification, data gathering and analysis, model creation, and implementation Strong understanding of artificial intelligence applications and methodologies, such as working knowledge
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 23 hours ago
perspectives, foster a stimulating research environment and advance knowledge within their fields. Postdocs are crucial members of our scientific research workforce, contributors to our research outputs and an
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, cognitive aging, or Alzheimer’s disease in rat models. Experience with quantitative analysis that integrates multiple types of biological data. FLSA Exempt Full Time/Part Time Full Time Number of Hours Worked
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, GDAL) and spatial databases. Knowledge of urban heat island analysis and/or flood risk modelling is a major asset. Experience in the development or the coordination of a web-based geospatial platform is
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, such as multi-objective optimization, model predictive control, mixed-integer optimization, stochastic optimization, energy management, or production scheduling. Good knowledge of integrated energy
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research including, but not limited to, constructing hypotheses, design and planning of research studies, data management, model development, conducting experiments or assessments, analysis and
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using codes in high level programming language such as python. Knowledge of earthquake source seismology observation/theory/modelling. Use of probability/decision trees and predictive models. Use of AI
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and apply AI and machine learning methods for signal processing, image analysis, data fusion, and prediction; · build physics-informed and hybrid AI models that combine geophysical knowledge with data