We are offering a fixed-term part-time position (65%) for three years, with the option to extend it to four years within the limits of the law. The intended starting date is January 2026. The position is subject to final funding approval.
Your tasks:
The research will focus on developing and testing methodologies to quantify and model peatland breathing using satellite optical and radar observations with machine learning algorithms. Peatlands are the largest natural terrestrial carbon store with an equivalent of half of the carbon that is in the atmosphere as carbon dioxide (CO2), and thereby they provide important ecosystem services for mitigating the effects of climate change. Peat breathing is the phenomenon of raising and lowering surface due to changes in the water level and can be regarded as a strong proxy for peatland condition and as an indicator of CO2 release. Peat breathing and resultant carbon fluxes are traditionally measured on a local scale and current methods don’t allow for a spatio-temporally comprehensive monitoring. In this research you will utilize satellite remote sensing, in particular radar technology and its integration with other observations. You will aim at three objectives: 1) to improve InSAR (Interferometric Synthetic Aperture Radar) methods for measuring long-term peatland motions as indicator for peat breathing on a large scale; 2) to correlate InSAR-derived peatland motions with field measurements; 3) to integrate all space-borne measurements into a machine learning model for improved mapping of CO2 release from peatland systems and validation with reference data from Eddy Covariance and chamber measurements.
You will be jointly supervised by Prof. Hanna Meyer from the University of Münster and Dr. Ling Chang from the University of Twente and you will benefit from complementary expertise in optical and radar remote sensing and work closely with both working groups. The place of work is Münster with regular research stays in Enschede.
This position is tied to working towards a doctorate.
Our expectations:
* You possess an MSc in geoinformatics, landscape ecology, geosciences or related fields, with experience in remote sensing, preferably InSAR.
* You work at the interface between environmental science and geoinformatics.
* You have strong computing skills, preferably in Python or R.
* You have demonstrated scientific creativity
* You have affinity with an interdisciplinary and multi-cultural education environment.
* You are willing to work in a Münster
* Twente collaboration project which involves regular travels between the partners
Advantages for you:
* Appreciation, commitment, openness and respect – values which are important to us.
* Our broad range of diverse work-time models offers great flexibility – also when working from home.
* If you have family members or young children in your care, our Family Service Office offers concrete support to help you balance your private and professional responsibilities.
* As an educational institution, we are deeply committed to offering occupational training and continuing education opportunities tailored to your individual needs.
* From A – Z, Aikido to Zumba, our sport and health programmes ensure a healthy work-life balance.
* As a university employee, you are entitled to numerous benefits afforded to public servants, e.g. an attractive company pension scheme ( VBL ), an annual end-of-year bonus and a position that is shielded from economic fluctuations.
The University of Münster strongly supports equal opportunity and diversity. We welcome all applicants regardless of sex, nationality, ethnic or social background, religion or worldview, disability, age, sexual orientation or gender identity. We are committed to creating family-friendly working conditions.
We actively encourage applications by women. Women with equivalent qualifications and academic achievements will be preferentially considered unless these are outweighed by reasons which necessitate the selection of another candidate.
If you have any questions, please contact Prof. Dr. Hanna Meyer ( hanna.meyer@uni-muenster.de ) or Dr. Ling Chang (ling.chang@utwente.nl ). Are you interested? Then we look forward to receiving your application by 2025-09-15. Applications should contain the usual documents (cover letter, CV, degree certificates) and be sent by email, as a single PDF, to: hanna.meyer@uni-muenster.de. Reference number: 2025_07_60