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Research Associate in Deep Learning

vor 4 Monaten

Duesseldorf, Deutschland Westfälische Wilhelms-Universität Münster Vollzeit

45,000 students and 8,000 employees in teaching, research and administration, all working together to shape perspectives for the future - that is the University of Münster. Embedded in the vibrant atmosphere of Münster with its high standard of living, the University’s diverse research profile and attractive study programmes attract students and researchers throughout Germany and from around the world.

The Department of Information Systems at the University of Münster, Germany, is seeking to fill oneor more positions of a

**Research Associate in Deep Learning**
**(PhD Student)**
**(salary level TV-L E 13)**

**The Project**
Managing and conserving forest ecosystems in Europe and worldwide is an indispensable component of climate adaptation and climate change mitigation strategies. Precise and up-to-date information about the health and the carbon balance of forests are, hence, critical to assess the current state of forests, trigger appropriate countermeasures against forest loss, and develop improved management strategies. Advances in both Earth observation and artificial intelligence have paved the way for the automation of forest monitoring using satellite time series data, including optical, radar, and LiDAR measurements. The forest maps produced by today's approaches, however, are still often limited to coarse resolutions and/or to relatively small spatial areas.

To overcome those limitations, the AI4Forest project brings together experts in artificial intelligence, applied mathematics, computer science, spatial remote sensing, and climate change. AI4Forest strives for both conceptually novel AI methods for forest monitoring as well as for scalable AI methods that allow to process large amounts of data efficiently and at low cost. The resulting techniques will facilitate the generation of detailed forest maps at a very high spatial and temporal resolution for the whole European continent and the entire world, including tree species identification down to the level of individual trees.

**Your Tasks**
Your core task will be to contribute to research and teaching activities related to the AI4Forest project. In particular, you are supposed to develop conceptually new machine learning models for analyzing large amounts of satellite data, efficiently and at low cost (e.g., novel tree segmentation models that require little computational resources). You will also work in a close collaboration with the AI4Forest project partners in both France (Laboratoire des Sciences du Climat et de l’Environnement; Centre National de la Recherche Scientifique) and Germany (Zuse Institute of Berlin; Technical University of Munich) as well as together with other international partners (e.g., University of Copenhagen). The position is tied to working towards a doctorate.

**Our Expectations**
- A graduate degree (MSc) in Information Systems, Computer Science, Geoinformatics, Geography,Mathematics, Physics, or similar is required.
- Knowledge in the field of machine learning, data engineering, and/or geographic informationsystems.
- Good programming skills, preferably Python.
- Good communication skills, as well as proficiency in spoken and written English are expected(knowledge of German is not required).

**Our Offer**
- The opportunity to engage in research within a highly relevant field with the goal of obtaininga doctoral degree.
- The opportunity to showcase your research findings at prestigious international conferencessuch as ICDE, ICML, KDD, VLDB, NeuRIPs, ICDM, and more.
- The chance for stays abroad at international partner institutes and universities (see project partners above).
- The opportunity to join a creative team at an aspiring university and in one of the most livablecities in Germany.

The University of Münster strongly supports equal opportunity and diversity. We welcome all applicants regardless of sex, nationality, ethnic or social background, religion or worldview, disability, age, sexual orientation or gender identity. We are committed to creating family-friendly working conditions. Part-time options are generally available.

**Prof. Dr. Fabian Gieseke**
**Machine Learning and Data Engineering**
**Department of Information Systems**
**University of Münster**
**Leonardo-Campus 3**
**48149 Münster