Postdoctoral Fellow (mwd) in remote sensing and machine learning

Eawag the Swiss Federal Institute of Aquatic Science and Technology is an internationally networked aquatic research institute within the ETH Domain (Swiss Federal Institutes of Technology). Eawag conducts research education and expert consulting to achieve the dual goals of meeting direct human needs for water and maintaining the function and integrity of aquatic ecosystems.

The Department of Systems Analysis Integrated Assessment and Modeling (Siam) is seeking a highly motivated

Postdoctoral Fellow (m / w / d) in remote sensing and machine learning

This position contributes to the HyperTails project an interdisciplinary initiative led jointly by the research groups on Human Environmental Systems Machine Learning and Complex Systems and Remote Sensing. The project develops novel AI-based methods to detect and classify mine tailings ponds worldwide using hyperspectral satellite imagery and contextual information extracted from mining literature. The aim is to establish the first global dataset linking spectral reflectance to contaminant profiles enabling scalable environmental risk screening of mine waste facilities.

We are looking for a motivated person at the post-doc level who will be involved in the following tasks :

• Develop object-based detection of tailings facilities using machine-learning architectures (e.g. YOLO) and multispectral imagery (Sentinel-2).
• Process and analyse hyperspectral imagery (EnMAP) and spectral libraries to extract diagnostic features.
• Apply natural language processing to extract contextual information from mining-related grey literature.
• Integrate spectral and textual data to infer contaminant profiles and environmental risks leveraging in-house expertise in inorganic chemistry and trace contaminants.
• Maintain Python-based workflows and GitHub repositories for the above tasks.

The successful candidate holds a PhD in remote sensing environmental science geology mineral exploration or computer science with proven expertise in in Python programming and version control and either hyperspectral remote sensing or machine learning (ideally both). Experience in machine learning and deep learning (e.g. PyTorch TensorFlow scikit-learn) natural language processing or information extraction from unstructured text or hyperspectral remote sensing techniques (spectral angles spectral unmixing continuum removal) is an asset. Excellent English communication skills analytical ability and an independent working style are expected.

Applications submitted by 10 December 2025 will receive full consideration and review will continue on a rolling basis until the position is filled. Applications must include a motivation letter a CV and contact information for two period of appointment is 12 months with the option to extend by another 12 months starting as agreed upon.

Eawag is a modern employer and offers an excellent working environment where staff can contribute their strengths experience and ways of thinking. We promote gender equality and are committed to staff diversity and inclusion. The compatibility of career and family is of central importance to more information about Eawag and our work conditions please consult and

For further information please contact Dr Marc Müller E-mail

We look forward to receiving your application. Please send it through this webpage as any other way of applying will not be considered. A click on the button below will take you directly to the application form.

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Eawag : Swiss Federal Institute of Aquatic Science and Technology

Key Skills

Virology,Bioinformatics,Genetics,R,Biochemistry,Cell Biology,Research Experience,Spectroscopy,Cell Culture,Molecular Biology,Microscopy,Research Laboratory Experience

Employment Type : Full-Time

Experience : years

Vacancy : 1