PostDoc in Optical and Microwave Remote Sensing of Forest Water Dynamics 80-100% (f/m/d)

WSL; Birmensdorf (ZH); On-site; CHF 90,000 - 110,000; Full time

Job summary

The Swiss Federal Institute for Forest, Snow and Landscape Research WSL invites applications for a PostDoc in Optical and Microwave Remote Sensing of Forest Water Dynamics. This 2-year position (with extension possible) is based at Pfynwald, Switzerland, starting February 2027 or by agreement.

You will develop retrieval methods for vegetation water content using SWIR, multi-frequency radiometry, and GNSS-T, integrate ground-based sensors, and collaborate with EPFL researchers to link remotely

Qualifications

• PhD in remote sensing, geophysics or related quantitative field.
• Strong background in optical and/or microwave remote sensing.
• Proficiency in Python or MATLAB for data analysis.
• Experience with multi-sensor data fusion and radiometry.

Responsibilities

• Develop and evaluate retrievals of vegetation water content from optical and microwave observations.
• Deploy and operate GNSS-T receivers and microwave radiometers.
• Process and analyze multi-sensor data at Pfynwald site.
• Collaborate with EPFL PERL Lab and publish results.

Skills

Python

MATLAB

Remote sensing

Data analysis

Scientific programming

Education

PhD in remote sensing or related field

Tools

GNSS-T receivers

Ground-based microwave radiometers

Spectroscopy

Job description

Swiss Federal Institute for Forest, Snow and Landscape Research WSL

The Swiss Federal Institute for Forest, Snow and Landscape Research WSL is part of the ETH Domain. Approximately 600 people work on the sustainable use and protection of the environment and on the handling of natural hazards.

The Remote Sensing group of the Land Change Science Research Unit at WSL is looking, in the framework of the HydraSense research project, from February 2027 or by agreement, for the duration of 2 years (with the possibility of extension), for a

PostDoc in Optical and Microwave Remote Sensing of Forest Water Dynamics 80-100% (f/m/d)

Climate-induced drought is increasingly threatening forest ecosystems, creating an urgent need for remote sensing approaches that can detect critical changes in tree water status and predict forest mortality. The HydraSense project aims to develop novel approaches combining optical and microwave remote sensing to monitor tree water dynamics and detect critical thresholds associated with drought-induced mortality. The project brings together expertise in remote sensing, environmental physics, and plant ecophysiology to advance our understanding and improve monitoring of forest responses to drought.
You will develop and evaluate approaches for retrieving vegetation water content from optical and microwave observations, including SWIR spectroscopy, multi-frequency (1.4-6.9 GHz) radiometry, and Global Navigation Satellite System Transmissometry (GNSS-T). You will contribute to the deployment and operation of GNSS-T receivers and ground-based microwave radiometers, along with in-situ measurements at the Pfynwald experimental forest site in Switzerland. You will process, analyze and integrate multi-sensor observations, investigate their sensitivity to vegetation water content and develop methods to disentangle water-related signals from structural effects using terrestrial laser scanning data. Working closely with experts in tree hydraulics at the PERL Lab of EPFL, led by Prof Charlotte Grossiord, you will relate remotely sensed signals to field and laboratory measurements of tree water status and hydraulic vulnerability. You will publish your results in international scientific journals and present them at scientific conferences.
You hold a PhD in remote sensing, geophysics, electrical engineering, environmental physics or a related quantitative discipline. You have a strong technical background in optical and/or microwave remote sensing, ideally with experience in spectroscopy, radiometry, electromagnetic modelling, or the processing and interpretation of multi-sensor observations. Proficiency in scientific programming (e.g., Python or MATLAB), quantitative data analysis, and the development of remote sensing retrieval methods is essential. Experience with field-based instrumentation, sensor calibration, or radiative transfer modelling is a strong asset. You are highly motivated to work at the interface of disciplines and to apply your technical expertise to questions in forest ecology and plant water relations. You enjoy collaborative research, are willing to participate in intensive field measurement campaigns, and demonstrate a high degree of independence, initiative and scientific curiosity.