Sort by
Refine Your Search
-
12.11.2025, Wissenschaftliches Personal Join our team in a collaboration between TUM and Politecnico di Milano! Develop cutting-edge methods combining remote sensing, physics-based modeling, and
-
this centre, we are opening a PhD position on remote sensing of mountain forest dynamics. The Technical University of Munich (TUM) is one of the leading universities globally. At the TUM School of Life Sciences
-
to receiving your application! If you have any questions about this position, please feel free to contact us by email. We will be happy to provide you with further information in advance. The position is
-
biology and AI-guided protein structure design are providing new insights into the structures of receptors responsible for food taste and odor perception and food-derived proteins. The project aims to make
-
to remote sensing and simu-lation modeling. A particular focus of our work is on mountain forest ecosystems. A quantitative understanding of ecosystem dynamics provides the foundation for the development
-
01.08.2025, Wissenschaftliches Personal For a scientific project for Spin-Selective Neutron Detection using Quantum Sensing, we are looking for a PhD Position (m/f/x) with 30h/week. The Technical
-
project and work environment: This research project addresses the profound impacts of environmental pollution on human health, specifically targeting how air- and foodborne pollutants may impair taste
-
, Geoscience, Remote Sensing, Hydrology, Data Science, Physics, or related fields • Experience in machine learning (ML), artificial intelligence (AI) or related fields • Software skills in ML languages such as
-
impact and adaptation analyses, and for spatio-temporal modelling as well as upscaling of ecosystem properties via remote sensing Interactive collaboration and exchange within the TUM Center for Forest
-
the perspective towards generating data for entrepreneurial seed funding (GO-Bio etc.) for a further development of the technology towards the market. In that sense we also highly encourage candidates that would be