Contribute to the development of the global MESSAGEix-GLOBIOM model, the open source MESSAGEix modeling framework, and related software tools and data sets; Coordinate data exchange and interoperability with other modeling tools connected to the IAM framework, including, but not limited to, models that are relevant for representing the financial sector in IAMs (e.g., financial risk models); Develop methods to bridge across spatial and sectoral scales when providing integrated assessment modeling outputs to finance sector users; Develop guidance and documentation of integrated assessment models and climate scenarios for users in the financial sector
Requirements:
PhD degree combined with relevant research experience in integrated assessment modeling, climate finance or related fields; Expertise and experience in processing large datasets, preferably in Python or R, is essential; Experience with frameworks for mathematical optimization (GAMS, pyomo, JuMP, etc.) and numerical solvers for large-scale problems; Demonstrated ability to contribute to open-source projects, data provision and code-development, preferably using git and GitHub
Text:
Research Scholar - Climate Scenarios for the Finance Sector Contribute to the development of the global MESSAGEix-GLOBIOM model, the open source MESSAGEix modeling framework, and related software tools and data sets; Coordinate data exchange and interoperability with other modeling tools connected to the IAM framework, including, but not limited to, models that are relevant for representing the financial sector in IAMs (e.g., financial risk models); Develop methods to bridge across spatial and sectoral scales when providing integrated assessment modeling outputs to finance sector users; Develop guidance and documentation of integrated assessment models and climate scenarios for users in the financial sector PhD degree combined with relevant research experience in integrated assessment modeling, climate finance or related fields; Expertise and experience in processing large datasets, preferably in Python or R, is essential; Experience with frameworks for mathematical optimization (GAMS, pyomo, JuMP, etc.) and numerical solvers for large-scale problems; Demonstrated ability to contribute to open-source projects, data provision and code-development, preferably using git and GitHub
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