Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Program
-
Field
-
financial shocks and risk persistence phenomena, and functional variables such as entropy (of various types) are introduced as metrics to quantify uncertainty and the concentration of risk dynamics. The
-
fields in cosmic voids and filaments. The candidate will reduce model uncertainties by producing new large cosmological simulations of the magnetic outputs from galaxies in the ENZO code, which will test
-
drought resilience and adaptation. Current groundwater flow models, however, often exhibit important uncertainties related to input parameters and boundary conditions. Reducing this uncertainty is difficult
-
of the Universitat Politècnica de València announcing a selection process for a fixed-term employment predoctoral contract within the framework of a Research Project Embracing uncertainty for document processing https
-
PhD project involves interdisciplinary research at the interface of computer science and mathematics and addresses a complex, coupled inverse problem with explicit uncertainty quantification. Research
-
%). You will work at the intersection of numerical analysis, uncertainty quantification, and scientific machine learning. The research will primarily focus on probabilistic methods for data-driven model
-
-fidelity analyses with observational data to yield robust, uncertainty-aware predictions. Outcomes include a transparent, open-source toolkit for catastrophic risk and fragility assessment, integration
-
., probability, analysis), eager to conduct cutting edge research in the field of uncertainty quantification, in particular the theory and methods known as predictive Bayes. Predictive Bayes theory involves
-
the effectiveness of integrated pest management and reduce uncertainty in decision-making processes. The researcher will be responsible for adapting and evaluating data acquisition systems, including modified
-
Description Overview: We are seeking a Postdoctoral Research Associate who will focus on creating innovative uncertainty quantification and visualization algorithms that enable trusted visual representation and