Context And Mission
The Earth Sciences Department at the Barcelona Supercomputing Center (BSC) (www.bsc.es) is embarking on an umbrella of large-scale activities and developments linked to the implementation of a High-Resolution Emission System for Air Quality Prediction and Greenhouse Gas Monitoring. These activities are part of a large initiative on the “Modernization of observation networks and digitalization of production processes for the development of intelligent meteorological services in the context of climate change” in the framework of the European Recovery, Transformation, and Resilience Plan funded by the European Union – Next Generation EU.
In this ambitious and potentially rewarding endeavor, we need a variety of postdoctoral researchers, researchers and research engineers in atmospheric composition, climate, machine learning/artificial intelligence and computer science.
The applicants for postdoctoral and research positions would ideally have interest in at least one of the following topics:
– Development of the BSC emission modeling framework (HERMESv3).
– Development of a near-real-time emission monitoring system for Spain.
– Development of satellite-based emission plume detection and quantification methods to estimate and monitor emissions from urban and industrial hotspots.
– Understanding of multi-phase organic chemistry and development of flexible schemes in atmospheric models.
– Understanding of aerosol microphysics and development of related parameterizations in atmospheric models.
– Design and development of machine learning/artificial intelligence models to emulate air quality models or components (e.g. chemical mechanism) and improve emission inversion estimates.
– Understanding the impact of vegetation fire emissions on ozone and particulate matter.
– Characterization of dust sources and mineralogy based on space-borne spectroscopy (e.g. EMIT, EnMAP).
– Improving our understanding desert dust emission and its variability and trends.
– Exploitation of in-situ and/or remote sensing observational data for atmospheric composition modelling, data assimilation, evaluation, and emission inversion.
The applicants for research engineer positions would ideally have interest in at least one of the following topics:
– Python developments for emission modeling and evaluation.
– Atmospheric composition/emission modeling performance and modularization.
– GPU porting/offloading for atmospheric composition/emission modeling.
– Workflow developments for operational forecasts and data assimilation.
– Parallel implementations for artificial intelligence model training and application on GPU/TPUs HPC environments
Very good interpersonal skills
Excellent written and verbal communication skills
Ability to take initiative, prioritize and work under set deadlines
Ability to work both independently and within a team