Research Associate on Land Surface Modeling in the MOMENTplus project § 28 Subsection 3 HmbHG
Research Associate on Land Surface Modeling in the MOMENTplus project § 28 Subsection 3 HmbHG
Research Associate on Land Surface Modeling in the MOMENTplus project § 28 Subsection 3 HmbHG
Research Associate on Land Surface Modeling in the MOMENTplus project § 28 Subsection 3 HmbHG
universität hamburg
Fach- und Hochschulen
Hamburg
- Art der Beschäftigung: Teilzeit
- 51.500 € – 64.000 € (von XING geschätzt)
- Vor Ort
- Zu den Ersten gehören
Research Associate on Land Surface Modeling in the MOMENTplus project § 28 Subsection 3 HmbHG
Über diesen Job
Research Associate on Land Surface Modeling in the MOMENTplus project § 28 Subsection 3 HmbHG
InstitutionFaculty of Mathematics, Informatics and Natural Sciences, Department of Earth System Sciences
Salary levelEGR. 13 TV-L
Start date01.05.2026, fixed for a period of three years (This is a fixed-term contract in accordance with Section 2 of the academic fixed-term labor contract act [Wissenschaftszeitvertragsgesetz, WissZeitVG]).
Application deadline15.03.2026
Scope of workpart-time
Weekly hours65 % of standard work hours per week
Your responsibilities
Duties include academic services in the project named above. Research associates may also pursue further academic qualifications outside of their work responsibilities. They may also pursue doctoral studies outside of working duties.
We are looking for an enthusiastic PhD student working in the project MOMENTplus (https://www.moment-permafrost.uni-hamburg.de/en/uebermoment.html). This PhD student will work on the new ICON-land model which includes the Jena Soil Model in order to address questions on the future Arctic methane budget and the effect of plant-microbe interactions on the C budget in permafrost-affected ecosystems. You will join a dynamic and growing group of field scientists and modellers with interesting research questions about Arctic ecosystems and related climate feedbacks. The candidate will be embedded into the School of Integrated Climate System Sciences at the University of Hamburg and the MOMENTplus consortium with seven German institutions. We expect you to integrate into these research environments, and to contribute to the ICON-Land model development.
Your profile
A university degree in a relevant field.
The ideal candidate has got experience in dynamic modeling approaches (land surface models, dynamic global vegetation models) or experience in using computer languages like FORTRAN or C. You are also familiar or interested in soil processes in northern high latitude ecosystems, and you like to present your research results at conferences and in peer-reviewed journals. We offer you a dynamic research environment where you are embedded into a larger group of modelers working on the same land surface model.
We offer
- Reliable remuneration based on wage agreements
- Continuing education opportunities
- University pensions
- Attractive location
- Flexible working hours
- Work-life balance opportunities
- Health management, EGYM Wellpass
- Educational leave
- 30 days of vacation per annum
Universität Hamburg—University of Excellence is one of the strongest research educational institutions in Germany. Our work in research, teaching, educational and knowledge exchange activities is fostering the next generation of responsible global citizens ready to tackle the global challenges facing us. Our guiding principle "Innovating and Cooperating for a Sustainable Future in a digital age” drives collaboration with academic and nonacademic partner institutions in the Hamburg Metropolitan Region and around the world. We would like to invite you to be part of our community to work with us in creating sustainable and digital change for a dynamic and pluralist society.
The University of Hamburg is committed to equity. Diversity enriches our university life, whether in our studies, research, teaching, education, or workplace. We therefore welcome all applications, regardless of gender, gender identity, sexual orientation, ethnic or social background, age, religion or belief, disability, or chronic illness.
Severely disabled and disabled applicants with the same status will receive preference over equally qualified non-disabled applicants.