Friedrich Schiller University is a traditional university with a strong research profile rooted in the heart of Germany. As a university covering all disciplines, it offers a wide range of subjects. Its research is focused on the areas Light—Life—Liberty. It is closely networked with non-research institutions, research companies and renowned cultural institutions. With around 17.000 students and more than 10.000 employees, the university plays a major role in shaping Jena’s character as a cosmopolitan and future-oriented city.

The Geographic Information Science group in the Department of Geography seeks to fill a

PhD Position in Artificial Intelligence in Desert Geomorphology

commencing on 01 June 2025

We offer a part-time position (75%) as a fixed-term position until 31 May 2028.

In the DFG-funded project “Desert Pavements: Assessing their Modulating Role in the Atmospheric Dust Cycle” (PIs: Prof. Brenning / Jena and Prof. Schepanski / FU Berlin), you will conduct cutting-edge interdisciplinary research that advances our knowledge of desert pavement distribution and characteristics by developing innovative geospatial machine-learning models that harness geomorphometric as well as remote-sensing data. Your research will directly feed into the dust emission and deposition models that are coupled into an aerosol-climate model developed in parallel in Prof. Schepanski's group at FU Berlin.

Your responsibilities:

• Develop machine-learning models for geomorphic distribution modelling / digital soil mapping of desert pavement in Namibia
• Process digital terrain models and remote-sensing imagery required by these models
• Collect field data at remote field sites in harsh environments through soil mapping and drone surveys, including field-work planning and data processing
• Supervise student research assistants and thesis students supporting your field and computational research
• Contribute to sharing your knowledge through publications, conference presentations, outreach activities and contributions to teaching
• Work towards the completion of a PhD based in the project’s research area

Your profile:

• Master's degree in geomatics, geographic information science, soil / environmental science, geography or a related field with an interest in modeling environmental systems
• Very good knowledge of geospatial machine learning / artificial intelligence and remote sensing is required, along with in-depth knowledge of geocomputing tools (R / Python, GIS software)
• Experience in geomorphological or soil science field work and drone surveys is an advantage
• Independent and self-motivated personality with excellent problem-solving skills
• Excellent interpersonal and communication skills suitable for an interdisciplinary and intercultural work environment
• Excellent English language skills

Are you hesitating because you don't meet one or some of our requirements? Please do not hesitate to apply and give us a chance to get to know you.

We offer:

• Integration into the ELLIS Unit Jena, an outstanding cluster of researchers in the fields of artificial intelligence and machine learning for Earth system science
• Comprehensive support for doctoral researchers through the Graduate Academy as well as our local and international network
• An exciting and varied scope of activities with field-based as well computational components and creative freedom
• University health promotion, a wide range of university sports activities and a family-friendly working environment with a variety of offers for families;
• Remuneration based on the provisions of the Collective Agreement for the Public Sector of the Federal States (TV-L) at salary scale EV-L E-13, including a special annual payment in accordance with the collective agreement as well as additional fringe benefits and 30 days of paid vacation per year.

The position is offered as a fixed-term position for a maximum of three years with the possibility of an extension if the project is renewed. This is a part-time position with 75% of the working hours of a full-time employee (i.e., 30 hours per week).

Candidates with severe disabilities will be given preference in the case of equal qualifications and suitability.

Are you eager to work for us? Then apply by 07.02.2025 using our online form.