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Applicant’s project: In this new pilot project we will test whether linking remote sensing/aerial top-down data with
bottom-up microbial and chemical data can enhance our understanding of the ecological drivers shaping the spatio- temporal variability of public health-related biomarkers. This project is a collaboration between TUM, the DLR (https://www.dlr.de/en/eoc/about-us/german-remote-sensing-data-center/geo-risks-and-civil-security/city-and-society) and the LGL (https://www.lgl.bayern.de). Specifically, this project builds upon the GIS-based surveillance structure we developed for wastewater-based epidemiology during the pandemic. This structure links the urban sewage network (catchment) and the connected population. In this project, we will test whether we can integrate and extend this framework into a 'One Health' context by combining the additional remote sensing data, which provides high-level, top-down information on various urban land uses, green spaces, roof runoff, building types, heat islands and air pollution, with the bottom-up data from wastewater biomarkers. This project will lay the groundwork for a future combined surveillance network integrating georeferenced wastewater and remote sensing data.
Our offer: The Technische Universität von München (TUM) is one of the most renowned universities in Europe. We
are offering excellent working conditions in a highly international research environment. The salary is in accordance
with the Public Sector Collective Agreement on Länder (TV-L E13 100%). The starting date of the position is not yet
defined and will be updated as soon as we receive the formal funding. We expect a starting date between September and December 2026.
Your application: Please send your application/letter of interest by electronic mail and preferably in one single pdf-
document to Christian Wurzbacher (c.wurzbacher@tum.de, +49 89 289 13797)
Postdoctoral researcher / research assistant (w/m/d) with experience in big data handling
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