Summary
The Space Research Organisation Netherlands (SRON) is seeking an ambitious, highly motivated, and result-driven Postdoctoral Scientist to join the Earth Science Group (ESG). You will contribute to the newly funded COGNITO project, which aims to develop the first global, satellite-based system for detecting and quantifying carbon monoxide ($CO$) emissions from major urban areas and industrial facilities (with a focus on the iron and steel sector) using TROPOMI observations and advanced machine learning.
Post-Doc in Atmospheric Science and Machine Learning, (SRON) Netherlands
Position Overview
| Attribute | Details |
| Designation | Post-Doc in Atmospheric Science and Machine Learning |
| Research Area | Atmospheric Sciences, Satellite Remote Sensing, Machine Learning, and Climate Policy |
| Location | Leiden, The Netherlands |
| Employment Type | Full-time (2 years, with a possibility of a 2-year extension) |
| Salary | Up to โฌ5,758 gross per month (NWO salary scale 10, commensurate with experience) |
| Application Deadline | September 1st, 2026 (First selection; open until filled) |
Eligibility & Qualifications
- Education: PhD in atmospheric sciences or a closely related discipline.
- Experience:
- Proven experience in the interpretation of atmospheric observations (e.g., satellite, aircraft, etc.).
- Practical experience applying machine learning techniques.
- Skills:
- Strong programming and data analytics skills.
- Highly developed proficiency in written and oral English.
- Ability to work effectively both independently and as part of a multidisciplinary team.
- Assets (Preferred but not required): Experience with research on atmospheric $CO$, transport modeling, and/or flux inversions.
Job Description & Key Responsibilities
As a Post-Doc in the COGNITO project, you will apply novel machine learning approaches to detect $CO$ plumes in global satellite observations from TROPOMI (and potentially Sentinel-5).
Your day-to-day responsibilities will include:
- Algorithm Application: Applying existing machine learning algorithms for automated detection of $CO$ plumes in satellite data.
- Database Curation: Building a global catalog of $CO$ emission events from 2018 onward.
- Emission Quantification: Quantifying emissions from major cities and iron/steel production facilities using in-house quantification tools.
- Temporal Analysis: Evaluating seasonal cycles, operational changes, and potential signatures of industrial decarbonization efforts.
- Model Assessment: Assessing emission quantification tools using atmospheric transport modeling.
- Comparative Research: Comparing satellite-derived emissions with bottom-up inventories and reporting systems.
- Dissemination: Publishing findings in leading international scientific journals and presenting research at conferences and stakeholder meetings.
What We Offer
- Excellent Benefits: An 8.33% end-of-year bonus and an 8% holiday allowance.
- Work-Life Balance: 42 days of vacation leave per year (on a full-time basis) and flexible working hours.
- Support & Growth: Commuting expense compensation, an excellent pension scheme, parental leave facilities, and ample training/personal development opportunities.
How to Apply
Interested candidates can submit their applications directly through the Working at SRON Portal.
For informal inquiries about the position, feel free to contact:
- Dr. Ivar van der Velde at I.R.van.der.Velde@sron.nl
- Prof. dr. Ilse Aben at E.A.A.Aben@sron.nl
Last Date to Apply: First selection of applications begins September 1st, 2026. The position will remain open until a suitable candidate is found.








