PhD project: Exploitation of street canyon observations for inner city air quality forecasts and emission optimization
Within the Institute for Energy and Climate Research – Troposphere (IEK-8) at Forschungszentrum Jülich we are seeking for a PhD candidate to work on the investigation of a prediction model for inner city air quality by data analytics methods.
The PhD candidate will develop, implement, and test data analytics methods (e. g. cluster analysis, support vector machines, deep learning) in order to derive inner city air quality forecasts from street canyon observations and regional scale air quality forecasts. Therefore, the candidate must handle, merge and exploit large amounts of data from atmospheric transport models, observations and other valuable information. Thus, observed urban pollution will be assessed and merged with modelled regional background pollution. The investigation of local traffic emission quantification will be a main contribution to this work.
For detailed information about the position and application procedures please see:
https://www.fz-juelich.de/SharedDocs/Stellenangebote/_common/dna/2019D-143-EN-IEK-8.html?nn=718260
Information on the graduate program HDS-LEE can be found here: https://www.hds-lee.de/
The applicants must hold a M. Sc. degree in physics, mathematics, meteorology, or related field and must have experiences in data science, big data analysis, deep learning methods, or high performance computing (HPC).