Postdoctoral researcher (f/m/d): Machine learning modeling for air quality

Helmholtz-Zentrum Dresden-Rossendorf
Görlitz (Stadt), Sachsen (DE)
Salary according to the German Collective Wage Agreement for the Civil Service (TVöD)
August 26 2020
Organization Type

Postdoctoral researcher (f/m/d): Machine learning modeling for air quality

The Center for Advanced Systems Understanding (CASUS) is a German-Polish research center for dataintensive digital systems research. We combine innovative methods from mathematics, theoretical systems research, simulations, data science, and computer science to provide solutions for a range of disciplines- materials science under ambient and extreme conditions, earth system research, systems biology, and autonomous vehicles.

CASUS was jointly founded in August 2019 by the Helmholtz-Zentrum Dresden-Rossendorf, the Helmholtz Centre for Environmental Research, the Max Planck Institute of Molecular Cell Biology and Genetics. the Technical University of Dresden and the University of Wroclaw. CASUS is located in the heart of Görlitz at the border between Germany and Poland. The CASUS start-up phase is hosted by the Helmholtz-Zentrum Dresden-Rossendorf and is financed by the Federal Ministry of Education and Research and the Saxon State Ministry of Science and Art.

The Department Earth Systems Research is looking for a Postdoctoral researcher (f/m/d) interested in machine learning modeling for air quality. The position can begin immediately, and the contract will be limited to 31 March 2022.

Scope of Your Job

The candidate (f/m/d) will contribute to a project to build a robust and reliable high-resolution air quality forecasting system for a city. The forecasting system is being designed as a decision-making tool for stakeholders, and to increase an awareness of urban air quality issues for city residents. In this project, the candidate will identify key factors affecting air quality using statistical and machine learning methods, as well as develop a deep learning-based air quality model to predict fine-scale air quality for a European city with heavy traffic emissions. The goal of this work is to provide robust, accurate, high-resolution air quality forecasting products for a city using a machine learning approach.


  • Identify key factors affecting air quality using statistical and machine learning methods
  • Develop a deep learning-based air quality model with the key factors identified
  • Provide 2D spatially resolved air quality forecasts over a city
  • Publish research results in peer-reviewed scientific or technical journals and present results at external conferences seminars and/or technical meetings
  • Collaborate with others in a multidisciplinary team environment to accomplish research goals
  • Pursue independent (but complementary) research interests and interact with a broad spectrum of scientists internally and externally


  • PhD degree in computer science or a closely related field
  • Excellent programming skills in languages such as Python with machine learning packages
  • Experience with research on one or more of the following topics: deep learning, time-series regression, geospatial data
  • Solid understanding on machine learning, especially deep learning
  • Strong motivation to work in a collaborative environment
  • Excellent communication skills in English and in a professional context (presentation of research results at scientific meetings, colloquial discussions, writing of manuscripts)

We offer:

  • A vibrant research community in an open, diverse, and international work environment

  • Scientific excellence and high quality of training, coaching, and mentoring programs according to the Helmholtz Doctoral Guidelines

  • Broad national and international science networks

  • Salary according to the German Collective Wage Agreement for the Civil Service (TVöD)

  • Comprehensive benefits package (30 vacation days per year, company pension plan (VBL), flexible working hours, in-house health management, relocation assistance).

Kindly submit your completed application (including a one-page cover letter, CV, academic degrees, transcripts, etc.) only via our Online-application-system.

For any questions, do not hesitate to ask:
Dr. Michael Bussmann Tel.: +49 3581 37523 11,
+49 351 260 2616,
Mrs. Weronika Mazur Tel.: +49 3581 37523 23,
+49 171 3635554,
Mrs. Inken Köhler Tel.: +49 3581 37523 10

Place of work:

Working hours:
39 h/week

30 September 2020