The position is for two years and is part of an interdisciplinary project involving computer and atmospheric scientists and targeting large-scale simulations simulations of atmospheric composition towards improving our understanding of climate processes and air quality.  The main focus is on leveraging parallelism, as offered by the cloud, to significantly speed-up the run-time of those simulations.

The project uses the GEOS-Chem 3D atmospheric simulation software (https://geoschem.github.io/) as its platform of choice, and the postdoc's first task will be to implement and deploy initial enhancements to the GEOS-Chem task scheduling sub-system, and benchmark their benefits across a range of configurations.  Based on the analysis of the results, this will be followed by exploring and realizing various algorithmic enhancements to the initial design towards further improving performance and ensuring robustness of the results across operational settings.

The postdoc will have the opportunity to contribute novel algorithmic and computational development of a leading open-source global model of atmospheric composition and will have access to many opportunities for career development through both active mentoring by the PIs and access to a range of institutional resources available to junior researchers.

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