PhD candidate on the topic of “AI-based hydrodynamic modeling”

12.10.2021, Wissenschaftliches Personal

The TUM Professorship for Data Science in Earth Observation is seeking a full-time PhD candidate on the topic of “AI-based hydrodynamic modeling”.

For our team, we are looking for a full-time

The TUM-Professorship for Data Science in Earth Observation develops innovative methods for information extraction from remote sensing data in close cooperation with the Department EO Data Science of the Remote Sensing Technology Institute of the German Aerospace Center (DLR). For this international, exciting, and cutting-edge environment, we are looking for a PhD candidate on the topic of modeling hydrological processes during heavy rainfall events in urban areas using machine learning technologies. This PhD position is funded via a BMBF project in cooperation with Potsdam University, KISTERS AG, Urbica UG, and the TUM Chair of Hydraulic and Water Resources Engineering.

Tasks Your duties will include:

• Literature research
• Designing, implementing, and evaluating novel machine learning approaches to model hydrological processes in urban areas
• Exchange with our scientific partners in hydrology
• Transferring the developed approaches to unseen areas; adaptation to real-time scenarios
• Publishing the developed approaches in international journals and conferences

Promising applicants have:

• A master’s degree in Computer Science, Hydrology, Geodesy, or related discipline
• Very good programming knowledge, preferably in Python
• Experience with state-of-the-art machine learning or data science technologies
• Experience with hydrological or remote sensing data is a plus
• Solid command of the English language both in written and spoken form (German language is a plus)

We offer the possibility to join a successful research group with outstanding international reputation (see www.sipeo.bgu.tum.de). Since the Professorship is established as a joint venture between TUM and DLR, it offers the attractive combination of university-style fundamental research directly linked to practically relevant major projects and pioneering satellite missions. Depending on the applicant’s profile and qualifications, the salary of the position will follow the TV-L pay scale up to E13. The Technical University of Munich wants to increase the number of female employees, i.e. qualified female candidates are explicitly encouraged to apply for this position. Severely disabled candidates will be preferred if they are essentially similarly qualified and suitable for the position. The position is limited to 3 years with option of extension and can basically also be a part-time position.

Interested candidates please send their documents, including CV and documentation of their academic education to [email protected].

Technical University of Munich
Data Science in Earth Observation
Prof. Dr. Xiaoxiang Zhu
Arcisstraße 21, 80333 München, Germany
Tel. + 49 89 289 22659
[email protected]
https://www.asg.ed.tum.de/sipeo/

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Kontakt: [email protected]