Join to apply for the Research Associate Position in Data Management and GeoAI role at Technische Universität München (Technical University of Munich) .
The professorship Big Geospatial Data Management concentrates on the methodology of acquisition, organization, compression, analysis, and visualization of georeferenced or geometric data on large scales. We put emphasis on methods of distributed computing, machine learning, image and text analysis, randomized data structures, high-performance computing, and quantum algorithms. Beyond this research, we aim to support computational thinking and computational problem-solving in the Earth sciences at large.
The position is fully funded (TV-L E13, 100%) by the German Research Foundation (DFG) and the intended research focuses on defining and measuring a spatial and spatiotemporal notion of quality for map data. We want to establish processes and tools allowing the acquisition of reliable and up-to-date information about the quality of open geodata through the combination of machine learning and multimodal remote sensing.
Payment will be based on the Collective Agreement for the Civil Service of the Länder (TV-L), E13.
If you are interested in working in our team, please send your application consisting of a motivation letter, curriculum vitae, copies of your degrees and transcripts, employment certificates, and any other relevant documents as a single PDF file to us no later than 18 December 2025 .
Email address:
Do not hesitate to contact Prof. Dr. Martin Werner ( ) for any questions you may have. If you apply in writing, we request that you submit only copies of official documents, as we cannot return your materials after completion of the application process.
The professorship Big Geospatial Data Management (TUM) strives to raise the proportion of women in its workforce and explicitly encourages applications from qualified women.
The position is suitable for people with severe disabilities. Applicants with severe disabilities will be given preference when all other factors are essentially the same in terms of suitability, competency, and professional performance.
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.
Mehr Information:
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VollzeitArbeitsmodell:
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Erfahrung:
2+ yearsArbeitsverhältnis:
AngestelltVeröffentlichungsdatum:
27 Nov 2025Standort:
München
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