Johannes Reiche
5 months ago
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Postdoc in Long-Wavelength Radar for Forest Disturbance Monitoring at Wageningen University & Research Wageningen University & Research in Netherlands
Degree Level
Postdoc
Field of study
Computer Science
Funding
This is a paid 3-year postdoctoral position at Wageningen University & Research. The salary is a gross €3,546 to €5,538 per month for a 38-hour work week (scale 10, Dutch universities CAO-NU). The contract starts as a one-year appointment and may be extended for the project duration, subject to performance and organizational circumstances. Additional benefits include sabbatical leave, study leave, partially paid parental leave, a year-end bonus of 8.3%, and an excellent pension scheme.
Deadline
Expired
Country
Netherlands
University
Wageningen University & Research

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About this position
Postdoctoral opportunity at Wageningen University & Research in long-wavelength radar for forest disturbance monitoring.
This 3-year postdoc is hosted by the radar remote sensing team within the Laboratory of Geo-information Science and Remote Sensing (GRS) at Wageningen University & Research, Netherlands. The project focuses on developing and validating radar methods for forest disturbance detection and near-real-time alerting using next-generation long-wavelength satellite missions, including NISAR, BIOMASS, and preparation for ROSE-L.
The research is centered on radar remote sensing, Earth observation, forest disturbance monitoring, time-series analysis, and scalable processing of large satellite datasets. The work includes preprocessing multi-frequency radar data from C-, L-, and P-band sensors, studying forest disturbance regimes across Europe, and supporting the operational RADD near-real-time alert system. Target disturbance types include harvest, fire, wind damage, bark beetle infestation, and deforestation.
The position is embedded in an international and interdisciplinary environment. You will collaborate with Prof. Cornelius Senf at TU Munich on European forest dynamics and with Dr. Maciej Soja at Wageningen Environmental Research. The team is led by Dr. Johannes Reiche at WUR.
Eligibility highlights: a PhD in Remote Sensing, Data Science, or a related field; strong radar remote sensing background; experience with radar satellite data and large Earth observation datasets; strong Python skills; experience with forest or land change dynamics; excellent English (C1).
Funding and conditions: this is a salaried postdoc position with a gross monthly salary of €3,546–€5,538 for 38 hours/week, plus standard Dutch university benefits. The initial contract is for one year and may be extended up to the full 3-year project duration.
Application deadline: 12 June 2026. Applications must be submitted via the WUR vacancy page.
Funding details
This is a paid 3-year postdoctoral position at Wageningen University & Research. The salary is a gross €3,546 to €5,538 per month for a 38-hour work week (scale 10, Dutch universities CAO-NU). The contract starts as a one-year appointment and may be extended for the project duration, subject to performance and organizational circumstances. Additional benefits include sabbatical leave, study leave, partially paid parental leave, a year-end bonus of 8.3%, and an excellent pension scheme.
What's required
A PhD in Remote Sensing, Data Science, or a related field is required. Applicants should have strong fundamentals in radar remote sensing, experience processing and analyzing radar satellite data, experience with large Earth observation datasets and scalable data processing workflows, excellent Python programming skills, experience with forest and/or land change dynamics, the ability to publish scientific research and communicate results effectively, experience working in interdisciplinary teams and with stakeholders, and excellent written and spoken English at C1 level. Preferred qualifications include experience with deep learning methods for Earth observation, European forest management and forest disturbance dynamics, and time-series analysis or near-real-time forest monitoring.
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