Research associate in the market of AI for Earth observation in Smart Cities Applications

24.06.2021, Wissenschaftliches Personal

The Professorship of Data Science in Earth Observation (Prof. Xiaoxiang Zhu) is seeking a research associate in the market of AI for Earth observation in Smart Cities Applications at the soonest possible date.

About us

The Professorship of Data Science in Earth Observation (Prof. Xiaoxiang Zhu) develops modern signal processing and AI solutions to extract geoinformation from big Earth observation data acquired by current and future Earth observation missions. It is involved in a large number of third-party projects and a large international network. It is a global leading group in the field of artificial intelligence in Earth observation (AI4EO). It is in closely collaboration with the Department of EO Data Science, Remote Sensing Technology Institute of the German Aerospace Center, with the German BMBF International Future Lab AI4EO, and with the Munich Data Science Institute, where Prof. Zhu is also leading.

Your mission

This position is funded by the ERC project AI4SmartCities that aims at technology transfer. The AI4SmartCities team is aimed to eventually create a spin-off company. The candidate is intended to conduct market research of AI for Smart Cities algorithms and applications. Therefore, the candidate may witness the creation of a start-up, and may become part of it. The tasks described below require specific knowledge and outstanding expertise. In order to meet the requirements of the position, extensive professional or research experience in the fields of Earth observation is required. The holder of the position will be responsible for the following tasks:

• Market analysis of the demand of geospatial information in the field of smart cities
• Documentation, and improvement of deep learning algorithms for real-world applications
• Communication and between other project members, the TUM technology transfer office (TUM ForTe), and the potential collaboration partners
• Support in project management and reporting

Your qualifications

• completed university degree (university diploma/master's degree) in computer science, geoinformatics, data science, business administration, or comparable field of study
• several years of professional experience in Earth observation research institute or industry, especially in market analysis of EO downstream applications
• Understanding of common AI algorithms in EO, and the ability to understand and summarize new algorithms
• excellent communication and cooperation skills, ability to interact with scientists at different levels
• good software design skills and the ability to write clean, and reusable code in machine learning, deep learning frameworks, such as Tensorflow and PyTorch, is a plus
• very good knowledge of spoken and written English language
• very good knowledge of spoken and written German language
• ability to work highly motivated and independently in a team

Other welcomed qualifications

• knowledge of signal processing algorithms for images, videos or audio is welcomed
• good graphic design skills with tools such powerpoint and photoshop is welcomed
• doctoral degree desired, but not necessary if qualification is sufficient
• experience in website design

Payment will be based on the Collective Agreement for the Civil Service of the Länder (TV-L, E13 level). TUM strives to raise the proportion of women in its workforce and explicitly encourages applications from qualified women. Applications from disabled persons with essentially the same qualifications will be given preference.

As part of your application, you provide personal data to the Technical University of Munich (TUM). Please view our privacy policy on collecting and processing personal data in the course of the application process pursuant to Art. 13 of the General Data Protection Regulation of the European Union (GDPR) at https://portal.mytum.de/kompass/datenschutz/Bewerbung/ . By submitting your application, you confirm to have read and understood the data protection information provided by TUM.

Kontakt: Interested candidate please send your motivation letter, CV, and supporting materials to Prof. Xiaoxiang Zhu (zhulab@lrg.tum.de). Please note, this is not a Ph.D. position. Ph.D. applicants, please refer to other positions offered by us.

More Information

https://www.lrg.tum.de/sipeo/home/