About Us:

The TUM Chair of Data Science in Earth Observation (SiPEO) develops innovative signal processing and machine learning algorithms to extract geo-information from big geospatial data, ranging from remote sensing satellite data, aerial data, LiDAR to social media data. As downstream applications, we provide large scale and highly accurate geo-information to address societal grand challenges, such as monitoring the global urbanization, climate research and supporting the sustainable development goals of the United Nations. Towards this goal, our chair hosts large scale initiatives, such as the international future lab AI4EO, the national excellence center ML4Earth and the TUM innovation network EarthCare, and thus, offers a close connection to a large AI4EO research team covering a wide range of expertise ranging from machine learning/deep learning, remote sensing and Earth observation, big data analytics, data mining, data fusion, HPC to sustainability. In addition, we offer analysis-ready data on a global scale that are either open and free, such as Sentinels, or accessible through scientific proposals or academic collaborations, such as TanDEM-X and Planet Scope.

Your Mission:

To establish the AI4EO for Social Good working group, our lab offers four open positions for outstanding postdocs and senior scientists (initially for two years with the possibility to prolongate).  Interested applicants shall share the vision of the working group. The main research tasks will be AI4EO for addressing the challenges of our time, building up on the expertise and data available at the chair. The exact topic will be defined jointly by the candidate and Prof. Xiaoxiang Zhu – the PI of the lab.

Interested applicants should have an excellent track record and a PhD in machine learning, computer science, statistics, remote sensing, mathematics or a related discipline. 

Application materials comprise:

−         CV

−         Full set of transcripts 

−         Statement of purpose

−         Briefly state what drives you and what are your goals in applying to the SiPEO lab

−         Names for at least two references (For each reference, please include name, title, and email address. References should expect to be contacted for a reference letter.)

Please submit these documents to zhulab@lrg.tum.de. Please kindly consider that due to the high requests, we will not be able to consider incomplete applications. 

Contact:

Prof. Xiaoxiang Zhu

Technical University of Munich
Chair of Data Science in Earth Observation
Arcisstraße 21
80333 Munich, Germany