August 2018
Message 83

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[Met-jobs] Postdoc on "Downscaling NO2 Satellite Observations using Machine Learning Algorithms" at Empa, Switzerland

From "Kuhlmann, Gerrit" <>
To "" <>
Date Tue, 28 Aug 2018 05:03:16 +0000

Dear all,


Our research lab at Empa (part of the Swiss ETH domain) is offering a 2-year postdoc position on:


Downscaling NO2 satellite observations using machine learning algorithms


Your tasks

*      Develop novel algorithms for downscaling NO2 observations from the recently launched Sentinel-5P satellite to high-resolution air pollutant maps using machine learning methods.

*      Compare the performance of the algorithms with traditional regression models, high-resolution air pollution models, and ground-based observations.

*      Publish results in scientific journals and present your work at international conferences.


Required skills

*      PhD degree in physics, environmental sciences, computational sciences or a related discipline.

*      Experience with machine learning algorithms, statistical regression models and large datasets.

*      Strong programming skills, e.g., Python, R, Linux shell scripting.

*      Knowledge of deep learning / machine learning libraries.

*      Experience in imaging remote sensing is advantageous.

*      Ability to communicate scientific results in peer-reviewed journals and conferences.

*      Fluency in English is required; basic knowledge of German is desirable.


The duration of this position is two years. The position is available from 1 November 2018 and will remain open until filled. Applications received before 15 September will receive full consideration. Working place will be Empa in Dübendorf.


For further details please see the attached file and visit the application page at:



Best regards,

Gerrit Kuhlmann





Gerrit Kuhlmann, Ph.D.

Laboratory for Air Pollution/Environmental Technology
Empa - Swiss Federal Laboratories for Materials Science and Technology
Überlandstrasse 129
8600 Dübendorf

Tel.:  +41 58 765 4753


Attachment: Empa_DownNO2.pdf
Description: Empa_DownNO2.pdf

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