PhD candidate on the topic of “AI-based hydrodynamic modeling”
☞ Technische Universität München
View: 205
Update day: 18-10-2024
Category: Information Technology
Industry: Bildung
Job content
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
PhD candidate on the topic of “AI-based hydrodynamic modeling”
About us 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
- 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)
Interested? Interested candidates please send their documents, including CV and documentation of their academic education to anna.kruspe@tum.de.
Technical University of Munich
Data Science in Earth Observation
Prof. Dr. Xiaoxiang Zhu
Arcisstraße 21, 80333 München, Germany
Tel. + 49 89 289 22659
xiaoxiang.zhu@tum.de
https://www.asg.ed.tum.de/sipeo/
Hinweis zum Datenschutz:
Im Rahmen Ihrer Bewerbung um eine Stelle an der Technischen Universität München (TUM) übermitteln Sie personenbezogene Daten. Beachten Sie bitte hierzu unsere Datenschutzhinweise gemäß Art. 13 Datenschutz-Grundverordnung (DSGVO) zur Erhebung und Verarbeitung von personenbezogenen Daten im Rahmen Ihrer Bewerbung. Durch die Übermittlung Ihrer Bewerbung bestätigen Sie, dass Sie die Datenschutzhinweise der TUM zur Kenntnis genommen haben.
Kontakt: anna.kruspe@tum.de
Deadline: 02-12-2024
Click to apply for free candidate
Report job
SIMILAR JOBS
-
⏰ 23-11-2024🌏 Munich, Bavaria
-
⏰ 16-11-2024🌏 Munich, Bavaria
-
⏰ 12-12-2024🌏 Herzogenaurach, Bavaria
-
⏰ 23-11-2024🌏 Munich, Bavaria
-
⏰ 12-11-2024🌏 Munich, Bavaria
-
⏰ 11-11-2024🌏 Munich, Bavaria
-
⏰ 12-11-2024🌏 Munich, Bavaria
-
⏰ 21-11-2024🌏 Munich, Bavaria
-
⏰ 17-11-2024🌏 Munich, Bavaria
-
⏰ 13-11-2024🌏 Munich, Bavaria