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the 01.10.2022. Your Responsibilities: You will work at the cutting edge of privacy-preserving deep learning research with a focus on one or more of the following topics: - Optimal model design for differentially
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autonomous systems Fluent English (spoken and written); German proficiency is a strong plus Ability to work independently, willingness to learn and acquire new competence Strong programming skills (Python, C
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bring together different disciplines and perspectives to foster the sustainable management of mountain forests in the Alps. The current position will be part of the Center for Forest Management in the Alps, and
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and optimizing building designs will be developed. The goal of this project is to develop a methodology for automatically checking building designs against regulations, and then provide reasoning about
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of visual interfaces Benchmarks, usability studies, and open-source visualization tools Visualization for explainable AI/LLM Development of functional research prototypes such as MetroSets Our work in this
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01.10.2025, Wissenschaftliches Personal This PhD position is part of the interdisciplinary TUM GNI project AUROrA – AI-Driven Urban Flood Resilience: Integrating Earth Observation and Architectural
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permanent funding as part of the German and Bavarian government's AI strategy. Our vision is to strengthen regional, national, and international competence in AI and to make the corresponding potential
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of mountain forests in the Alps. The current position will be part of the Centre for Forest Management in the Alps, and will work in the subproject 4, remote sensing of mountain forest dynamics (Prof. Dr
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exclusion study in Southern Germany which has undergone long-term drought treatments since 2014 (KROOF: https://www.lss.ls.tum.de/en/lsai/kroof/). You will use this unique experimental setup, in which drought
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space. We quantify these changes, identify their causes and describe their impacts on biodiversity and ecosystem ser-vices. To do this we use a combination of diverse methods, from empirical research