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Helmholtz-Zentrum Hereon

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Postdoctoral Researcher in Probabilistic Deep Learning for Urban Air Quality (AEON-UP) Helmholtz-Zentrum Hereon in Germany

Degree Level

Postdoc

Field of study

Computer Science

Funding

Full funding available

Deadline

Mar 9, 2026

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Country

Germany

University

Helmholtz-Zentrum Hereon

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Keywords

Computer Science
Environmental Science
Air Quality Management
Earth Science
Uncertainty Analysis
Air Pollution
Ecological Modeling
Statistics
Geospatial Information
Physics
ML

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About this position

Postdoctoral Researcher in Probabilistic Deep Learning for Urban Air Quality (AEON-UP) at Helmholtz-Zentrum Hereon, Geesthacht, Germany.

This postdoctoral opening sits at the interface of Environmental Science, Computer Science, Earth Science, Physics, and Statistics. The project develops a transferable AI system for high-resolution urban air quality prediction across European cities, combining physics-based chemistry transport models (CTMs) with probabilistic deep learning, especially neural processes.

The successful candidate will work on scalable data infrastructure, multimodal geospatial data, neural-process architectures for spatio-temporal prediction, uncertainty quantification, model benchmarking, and transfer to new cities. The role also includes training models on HPC systems, publishing results, and contributing to open-source releases.

Required background: a PhD in Machine Learning, Computer Science, Physics, Environmental Sciences, or a related field; experience with deep learning frameworks such as PyTorch; strong Python programming skills; and motivation to work on complex real-world problems with societal relevance. Helpful experience includes probabilistic/Bayesian methods, spatio-temporal or geospatial data, and HPC.

Funding is through a salaried full-time research position (39 h/week) for 2 years, with remuneration up to pay group 13 under the German public-service collective agreement, plus standard benefits. The application deadline is 2026-03-09. Work location: Geesthacht, Germany.

Supervisory contacts mentioned in the post include Dr. Martin Ramacher and Dr. Matthias Karl.

Funding details

Full funding including tuition fees and living expenses is available for this position. The scholarship covers all educational costs and provides a monthly stipend.

How to apply

Please submit your application including a cover letter, CV, academic transcripts, and contact information for two references. Applications should be sent via the online portal before the deadline.

More information can be found here

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