PhD position in deep learning for glacier monitoring

4‑Year PhD Position – M3OCCA Program (Erlangen, Germany)

A fully-funded 4‑year PhD position is available starting June 01 2026, in Erlangen, Germany, as part of the M3OCCA program.

The research topic involves developing deep learning methods to improve robustness and adaptability in glacier surface and bedrock detection from radargrams. The research will focus on continual learning for incremental adaptation to new data and foundation models for robust generalization across diverse glaciers, sensors, and environments.

Postdoctoral Researcher – Digital Twin of Boreal Forest Structure (Natural Resources Institute Finland)

Natural Resources Institute Finland (Luke) is hiring a postdoctoral researcher for the “Digital Twin of Boreal Forest Structure” project, focusing on developing machine learning methods for large‑scale, tree‑level forest mapping using remote sensing data for biodiversity.

PhD Student – Sustainable and Resource‑Efficient Machine Learning (Linköping University)

Linköping University is seeking a PhD student to research sustainable and resource‑efficient machine learning, focusing on methodologies to reduce computational, energy, and storage demands, and associated carbon emissions, while maintaining model quality.

Fully‑Funded PhD Fellowship – Greenhouse Gas Flux Modeling (University of Copenhagen)

The University of Copenhagen is offering a fully‑funded PhD fellowship at its Department of Computer Science, focusing on developing novel machine learning methods to model greenhouse gas fluxes from wetlands using remote sensing and ground‑level measurements for climate change mitigation.