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against hourly wind and wave time series spanning the project lifetime, with Monte Carlo simulation over weather years and component time-to-failure. The models are currently implemented in MATLAB with
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Additional Information Eligibility criteria - Remote sensing (applied to tropical forests) - Knowledge of (tropical) climatology is an advantage - Statistical analysis of time series (correlations, composites
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 1 month ago
desirable. Candidates with experience in time-series machine learning, advanced data analytics, and programming (Python) are especially encouraged to apply. Special Physical/Mental Requirements Special
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notification. 12. Application period: The competition is open from 08/24/2026 to 09/04/2026. 13. Application Submission Method: Applications can be submitted through the UPB application submission portal (http
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Title of the Position: Postdoctoral Associate Department and School: Child Study Center, Yale School of Medicine Anticipated Appointment Dates: Mid 2026 Email/Website: https://medicine.yale.edu
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equations, numerical analysis, mathematicalmodels in biomedicine, biostatistics, machine learning, statistical learning, multivariate statistics, time series,mathematical modelling, generalized linear models
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, with flexible start dates. As a TRAILS Postdoctoral Associate, you will have the opportunity to pursue your own research agenda, interact with our Institute’s diverse array of researchers, and contribute
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of the platform, as it will help them reduce the time needed to find proper employees or adapt their curricula to the requirements of the market. Based on the results of the analyses, a series of recommendations
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the use of the platform, as it will help them reduce the time needed to find proper employees or adapt their curricula to the requirements of the market. Based on the results of the analyses, a series of
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discovery through integrative approaches. Time-series and longitudinal multi-omics data analysis for disease progression modeling. Explainability and interpretability of AI models to support clinical decision