Stefan Oehmcke
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PhD Researcher / Research Assistant in Machine Learning for Earth Observation University of Rostock in Germany
Degree Level
PhD
Field of study
Computer Science
Funding
Full-time position funded at TV-L E13 for 3 years.
Deadline
Oct 15, 2026
Country
Germany
University
University of Rostock

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About this position
Stefan Oehmcke, Junior Professor for Machine Learning at the University of Rostock, is hiring a PhD researcher / Research Assistant in Machine Learning for Earth Observation. The position is based in the VACOT group at the University of Rostock in Rostock, Germany, and involves close scientific collaboration with Ankit K. at the University of Copenhagen.
The research focus is methodological machine learning motivated by challenging Earth observation and Earth-system problems, especially interactions between heatwaves on land, in coastal waters, and the atmosphere. Possible directions include multimodal and multiscale representation learning, learning from heterogeneous, irregular and missing observations, geometric deep learning for spatial and temporal interactions, and transfer learning plus probabilistic modelling under changing regions and data availability.
The post is intended for candidates who want to publish methodological work at leading international ML and computer vision conferences. A background in remote sensing is helpful but not required; the key requirement is a strong foundation in machine learning and interest in research driven by real Earth-system applications.
This is a 3-year, full-time position with TV-L E13 funding and leads to a PhD (Dr.-Ing.). The application deadline is 15 October 2026. Interested applicants should use the job description/application link provided in the post.
Funding details
Full-time position funded at TV-L E13 for 3 years.
What's required
A strong foundation in machine learning is preferred. A background in remote sensing is useful but not required. The post is aimed at PhD-level candidates (Dr.-Ing.) and is full-time for 3 years.
How to apply
Review the job description and application page, then submit an application through the linked University of Rostock posting. Share the opportunity with interested MSc students or graduates if appropriate.
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