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accessibility), and clinical data. * Develop, apply, and benchmark machine learning and statistical models for subtype discovery, classification, and outcome prediction. * Contribute to the development
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About the Opportunity Summary: Research involves developing and implementing material models to predict microstructure, phase change and residual stress in processes in high energy processes in
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paired with computational biology and machine learning to develop predictive AI models of how cells interpret and respond to the surrounding extracellular matrix. Required Qualifications: We are looking
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teams. Unit URL https://imci.uidaho.edu/ Position Qualifications Required Experience Experience with statistical or predictive modeling as demonstrated by publications in the field Evidence of strong
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to validate predictions made by their machine-learning models and drive wet-lab discoveries. The candidate may also have opportunities to work with research software engineers to translate their research
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not limited to) identifying effective tutoring practices, running experiments on AI tutors in simulated and real-world environments, fine-tuning AI models to classify qualitative data, and building
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/2026 Back to Search Postdoctoral Research Associate, Electrical Resistivity Tomography and Environmental Geophysics Posting Number req26727 Department Biosphere 2 Department Website Link https
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chemical transport model (CTM). These geospatial inputs and information will be used to fine-tune a NASA foundation model (Prithvi WxC) to emulate CTM processes, and to predict ground-level air quality data
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, engineering, physical or life sciences. ● Demonstrated experience with laboratory experiments (design, conduct, analysis). ● Demonstrated experience in modeling (formulating equations, and computing predictions
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, or digital health. Responsibilities The Postdoctoral Scholar will: Analyze large-scale datasets from cohorts and clinical trials, including longitudinal data. Develop and implement predictive models