Helmholtz-Zentrum Hereon

The Helmholtz-Zentrum Hereon conducts cutting-edge international research for a changing world: Around 1,000 employees contribute to the tackling of climate change, the sustainable use of the world's coastal systems and the resource-compatible enhancement of the quality of life. From fundamental research to practical applications, the interdisciplinary research spectrum covers a unique range.

Institute of Coastal Environmental Chemistry

The Institute of Coastal Environmental Chemistry investigates the occurrence and fate of pollutants in the marine environment. Hereon offers a unique chemical-analytical infrastructure with which researchers can analyze environmental samples and quantify pollutants. Additionally, the institute has complex methods for modelling sources, transport and distribution.

Postdoctoral Researcher – Probabilistic Deep Learning for Urban Air Quality (AEON-UP)

JobID: 1056 – 2026/KU 2
Location: Geesthacht
Application deadline: 03 September, 2026

Project start October 01, 2026 until September 30, 2028.

Air pollution remains one of the major environmental health challenges in urban areas. At the same time, observations are often sparse and unevenly distributed. In the AEON-UP project, we develop a transferable AI system for high-resolution urban air quality prediction across European cities and combine:

• physics-based chemistry transport models (CTMs)
• with probabilistic deep learning methods, in particular neural processes

to generate spatially resolved predictions of NO2, PM2.5, and ultrafine particles (UFP), including uncertainty estimates.

You will work on extending neural processes to large-scale, multimodal geospatial data, a setting that remains largely unexplored in current machine learning research.

You will join an interdisciplinary project team at the interface of environmental modelling and modern Al.

At Hereon, the research group combines:

• long-standing expertise in urban air quality modelling
• with growing activities in machine learning and data-driven methods

You will work closely with:

• Dr. Martin Ramacher (machine learning for environmental applications)
• Dr. Matthias Karl (urban air quality modelling and emissions) and collaborate within a Helmholtz-wide network with expertise in:
• Bayesian deep learning neural processes (Helmholtz Munich)
• air quality measurements and exposure science (RIFS Potsdam)

We value a collaborative, inclusive, and respectful working environment and actively encourage diverse perspectives in research.

Equal opportunity is an important part of our personnel policy. We would therefore strongly encourage qualified women to apply for the position. In principle, the full time position (39 h/week) is also shareable and limited to 2 years, starts at 1st of October 2026.