The Laboratory for Air Pollution / Environmental Technology has an opening for a
The Atmospheric Modelling and Remote Sensing group at Empa (http://www.empa.ch/web/s503/) is looking for a highly motivated PhD candidate to work in the field of NO2 remote sensing and radiative transfer modelling within the project HighNOCS funded by the Swiss National Science Foundation. HighNOCS is a joint project with the Ludwig-Maximilians-University Munich (LMU) and the University of Zurich (UZH). The project aims to estimate high-resolution distributions of near-surface NO2 concentrations by combining NO2 columns from an imaging spectrometer flying on an airplane with high-resolution dispersion modelling and three-dimensional radiative transfer modelling.
The PhD student will extend the MYSTIC radiative transfer model (http://www.libradtran.org) for simulating 3D radiative transfer in the urban canopy and use APEX imaging spectrometer (http://www.apex-esa.org/) observations for estimating near-surface NO2 concentrations. The student will rely on the extensive expertise of the project team in the development and application of remote sensing, radiative transfer and air quality modelling. The position is immediately available for a candidate with an excellent master’s degree in physics, environmental sciences or a related discipline. Furthermore, a strong interest in remote sensing and programming (e.g. C, python) are required. We expect excellent English language skills; knowledge of German is advantageous.
We offer a highly stimulating research environment with excellent infrastructure and broad interdisciplinary surrounding. Working place will be at Empa in Dübendorf. A six-month exchange at LMU is planned at the end of the first year. The PhD student will be registered at theSwiss Federal Institute of Technology in Lausanne (EPFL)at the Environmental Remote Sensing Laboratories (Prof. Alexis Berne) and will obtain his or her degree from EPFL. The appointment can start immediately, preferably before April 2018. Applications submitted before 15th November 2017 will be fully considered.