Postdoc: Weakly Supervised EO ML for Climate Impact

RISE Research Institutes of Sweden; Göteborgs kommun; On-site; SEK 420,000 - 540,000; Full time

Job summary

RISE Research Institutes of Sweden in Gothenburg seeks a postdoctoral researcher to develop an advanced ML framework for weakly supervised Earth observation, aimed at identifying and quantifying the physical and socio-economic impacts of climate extremes from satellite imagery.

The project focuses on data-efficient change detection for geospatial foundation models, leveraging multi-sensor data and uncertainty quantification to produce reliable, decision-relevant estimates for climate adaptation

Qualifications

• PhD in a quantitative field (as listed).
• Strong Python skills with proven experience in PyTorch or TensorFlow.
• Excellent written and spoken English communication.

Responsibilities

• Develop annotation-efficient, weakly supervised ML models for EO using satellite data.
• Incorporate uncertainty quantification (e.g., SNGP) and robust change-detection capabilities.
• Collaborate with interdisciplinary teams across ML, climate science, and infrastructure research.

Skills

Deep learning

Spatio-temporal modeling

Remote sensing

Education

PhD in CS/ML/Data Science/Applied Math/Physics

Tools

PyTorch

TensorFlow

Job description

RISE Research Institutes of Sweden in Gothenburg seeks a postdoctoral researcher to develop an advanced ML framework for weakly supervised Earth observation, aimed at identifying and quantifying the physical and socio-economic impacts of climate extremes from satellite imagery.

The project focuses on data-efficient change detection for geospatial foundation models, leveraging multi-sensor data and uncertainty quantification to produce reliable, decision-relevant estimates for climate adaptation