Science manager in new center for Machine Learning in Earth Observation (ML4Earth)

06.12.2021, Wissenschaftliches Personal

AI methods, and especially machine learning (ML) with deep neural networks have replaced traditional data analysis methods in recent years. The Technical University of Munich (TUM), together with the German Aerospace Center’s Remote Sensing Technology Institute, has created the biggest European research team on AI for Earth Observation (AI4EO) over the past few years.

Starting in 2022, we will begin establishing a national ML4Earth center of excellence with high visibility. It will conduct own research at the highest international level by tackling fundamental methodical challenges in AI4EO and their application to the European mission of a Digital Twin Earth. ML research directions will include physics-aware machine learning, reasoning, uncertainty estimation, Explainable AI, Sparse Labels and Transferability, as well as Deep Learning for Complex Structures. These novel methods will be applied to practical tasks such as predicting European water storage, quantifying permafrost thawing, sea level budget, climate and earth system modeling, soil parameter mapping, and multi-sensor segmentation, together with our partners at renowned international and national institutes such as Bonn University, Alfred Wegener Institute, University of Bristol, Leipzig University, and the German Aerospace Center.

Another important goal of the project is international community building within the AI4EO domain. Aspects of this include the creation of benchmark data sets for a wide range of application scenarios, as well as educational opportunities for interested scientists and expert workshops. Our aim is the democratization of AI4EO to enable more researchers to exploit Copernicus and other EO data sources.

To establish this new center, we are seeking a science manager whose tasks will include handling the daily business of the project, coordinating tasks between center members, communicating with partners and funding agencies, and representing the center to other parties. In addition, independent, scientific research on the topic of ML for Earth observation will be supported.

Requirements:

• PhD in computer science, geoinformatics, data science, business administration, or comparable field of study
• professional experience in Earth observation and/or Data Science
• Background of general AI Methods, ideally applied on EO data
• very good knowledge in the area of scientific project application as well as the German research landscape
• good experience in the field of scientific communication ('Science Communication')
• experience in project management
• fluent command of the German language and very good knowledge of the English language, both written and spoken
• excellent communication and cooperation skills, ability to interact with scientists at different levels
• ability to work highly motivated and independently in a team

Kontakt: zhulab@lrg.tum.de

Mehr Information

https://www.asg.ed.tum.de/sipeo/home/