Scientist (Postdoc) in Earth Science
Scientist (Postdoc) in Earth Science
SRON - Netherlands Institute for Space Research
Leiden, Netherlands
Are you our new colleague?
Are you an ambitious post-doctoral scientist with strong machine-learning skills and experience in atmospheric remote sensing and data processing? Then you are the person we are looking for.
You and SRON Netherlands Institute for Space Research
The satellite mission Sentinel-5 (S5) is set to launch in 2026. This mission is part of the Copernicus programme, using Earth observation to monitor the atmosphere for climate and public health interests. SRON has a co-leading responsibility in the successful TROPOMI instrument on the Sentinel-5 precursor mission that is operational since 2018. SRON has been involved in the development of the Sentinel-5 mission from the science definition, to contributing key elements of the instrument and the data-reduction algorithms. You will work in the Level 2 team at SRON where we apply trace gas retrieval to measure concentrations of CO, CO2, and CH4 in the Earth’s atmosphere. These data products will be used further by modellers to determine emissions estimates. Such data is invaluable for climate change research, and fundamental to informing policymakers to help pave the way toward mitigation and adaptation approaches.
Your position and team
You will be part of our team of eight scientists working on trace gas retrieval in the Earth Science Group (ESG) of SRON. The ESG consists of approximately 30 scientists (permanent, postdocs, PhD students) who work on the data processing and interpretation of satellite instruments as well as the definition of new instrumentation and guiding the development. Our team develops algorithms for trace gas remote sensing, for operational data processing and validation, and gives scientific guidance during the implementation phase of future missions.
Your project
You will work on developing a CO2 data product from Sentinel-5, an innovative project that will be a unique step beyond the current state of the art set by TROPOMI . You will perform this work within our SRON team in close collaboration with our project partners, GRASP for the European Space Agency. Your tasks will include:
- Using machine learning techniques to improve the data quality through quality filtering and correcting biases between satellite and ground-based measurements.
- Developing a radiative transfer model to calculate absorption spectra from the atmosphere using AI tools.
- Using machine learning to model cloud information from synthetic satellite measurements to improve the efficiency of the retrieval workflow.
You will present your results to the project team, our external colleagues, at conferences, and in peer-reviewed journals.
Position requirements
We are looking for a person with a PhD in (atmospheric) physics or machine learning. Very good programming skills in Python, C++ and/or Fortran are required, and experience in deep learning is a clear asset. Good English language skills (speaking and writing) and the ability to work in a team and independently are necessary for this position.
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