Research Scientist for Soil-Vegetation-Atmosphere Interactions under Climate Extremes (f/m/x)
Helmholtz-Zentrum für Umweltforschung GmbH - UFZ

Temporary

Full Time, Part Time

Apply by: 2025-12-14

Published: 2025-11-18

Leipzig

I am interested

The UFZ has a strong commitment to diversity and actively supports equal opportunities for all employees regardless of their origin, religion, ideology, disability, age or sexual identity.
We look forward to applications from people who are open-minded and enjoy working in diverse teams.

Place of work:
Leipzig, Mobile working possible up to 3 days/week.

Working time:
100%

The job position is available for full-time or part-time employment.

Contract limitations:
limited contract/36 months

Salary:
Remuneration according to the TVöD public-sector up to pay grade 13 including attractive public-sector social security benefits.

Application deadline:
14.12.2025

Your contact for any questions you may have about the job:

Jian Peng
jian.peng@ufz.de

Please submit your application via our online portal with your cover letter, CV (please omit your photo, age, or marital status) and relevant attachments.

Apply now

More information about jobs at the UFZ:

www.ufz.de/career

Helmholtz-Zentrum für
Umweltforschung GmbH – UFZ
Permoserstraße 15
04318 Leipzig, Germany

The Helmholtz Centre for Environmental Research (UFZ) with its 1,100 employees has gained an excellent reputation as an international competence centre for environmental sciences. We are part of the largest scientific organisation in Germany, the Helmholtz Association. Our mission: Our research seeks to find a balance between social development and the long-term protection of our natural resources.

Research Scientist for Soil–Vegetation–Atmosphere Interactions under Climate Extremes (f/m/x)

The job

We are seeking a highly motivated research scientist to join our team (www.ufz.de/remote-sensing) working at the interface of soil, vegetation, and atmosphere interactions. The successful candidate will contribute to advancing process understanding and modelling of ecosystem responses to climate extremes (e.g., droughts, heatwaves, compound events). The position offers the opportunity to collaborate in an interdisciplinary environment and to link field data, remote sensing, and process-based or machine learning models. The position is for 3 years with the possibility of extension.

Your tasks

Investigate soil–vegetation–atmosphere dynamics under climate extremes using modelling approaches and observational data (in-situ and remote sensing)
Develop and apply methods to quantify the impacts of extreme events on soil moisture/temperature, vegetation functioning, and land–atmosphere feedbacks
Publish results in peer-reviewed journals and present findings at international conferences
Collaborate with colleagues and external partners in interdisciplinary projects
Contribute to proposal development and student supervision where appropriate

We offer

The freedom to master even the most demanding challenges between basic research and practical application
The chance to work in interdisciplinary, international teams and benefit from a variety of perspectives
Firstclass integration into national and international research networks to work together on global challenges
Excellent research infrastructure and research data management to optimally support your work
Flexible working hours and a wide range of options for balancing work and care responsibilities through our family office
Competent support and advice for international colleagues arriving at the UFZ from the 'International Office'
Special annual payment, capital-forming benefits and subsidised Germany Job Ticket
A workplace in a vibrant region with a high life quality and social and cultural diversity

Your profile

PhD (or near completion) in Meteorology, Remote Sensing, Hydrology, Earth System Science, Ecology, or a related field.
Strong background in land–atmosphere interactions, soil hydrology, vegetation dynamics, or climate extremes.
Experience with remote sensing, land surface models, or machine learning is highly desirable.
Proven track record of publications in relevant fields.
Strong programming skills (e. g., Fortran, Python, R, MATLAB) and experience handling large datasets.
Excellent written and oral communication skills in English, with the ability to work independently and in a team.