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on two core but complementary areas: Computer vision and sensor data analysis, applied to tasks such as object detection in drone images (e.g., pest or disease detection), object tracking (e.g. leaves
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ability to work in an interdisciplinary manner Creativity and a strong spirit of discovery to develop new research approaches Experience in planning and conducting experimental studies Very good data
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The TUM School of Computation, Information and Technology at the Technical University of Munich (TUM) welcomes applications for a PhD or Postdoc Position (m/f/d, 100%, 2 years+) in Numerical Mathematics
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programming skills with python Comprehensive knowledge of data science, data analysis, data management as well as machine learning Experience with data-driven machine learning (SINDY, LASSO, SISSO packages
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). The empirical research should capture and analyze teaching and learning processes, for example by video analysis or eye-tracking. Development activities for instance may include AI tools, the creation
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mesoscopic scale with a focus on X-ray and neutron diffraction as well as PDF analysis, supported by complementary experimental techniques or theoretical simulations Hands-on participation in experiments
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its detailed analysis through Oxford Nanopore Technologies (ONT). Your role will be central in creating and applying bioinformatics and machine learning tools to analyze long-read data and decipher cap
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: An essential aspect of this position is the analysis of neuroimaging data (primarily EEG) in the context of the study of attention and memory. Here, we focus primarily on the investigation of working memory and
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along different design options (reward payment paid out as loans or transfer to governments or as universal cash transfers to populations) Applied optimal taxation theory analysis to assess potential tax
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to environmental changes in the ocean and what effects this has on ecosystems and biogeochemical cycles, particularly the uptake and storage of carbon dioxide in the sea. Methods used include the analysis