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an exceptional international team with expertise in all aspects of the project. Your tasks will include: • Preparation of different EO and in-situ datasets for training a machine learning model • Development of ML
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measurements in a team of experts on and in the pyramids and creating digital object models with numerical simulations, for example, using Salvus software or similar. Publication of research results and
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application from qualified women. About the position The position involves both teaching and engaging in innovative research projects on tractor autonomy, path-planning algorithms, soil compaction modeling, and
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expertise in employing synthetic microbial communities, gnotobiotic mouse infection models as well as in molecular microbiology of gut microbiota and enteric pathogens. The TUM School of Life Sciences
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cellular biology, the project will investigate signal transduction mechanisms at the protein and membrane level. Experimental systems will include 2D cell culture, organoid models, and advanced biophysical
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-Checking, Argument Mining, Automated Planning, and Decision-Making. Training, domain adaptation, and evaluation of cutting-edge LLMs and Multi-Modal models in the cloud and on premise. Software Engineering
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distribution within body organs. We are looking for a PhD student (m/f/d) to start at the TUM in September or later. Your Task From animals’ circulatory system to random porous media in fuel cells, morphological
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robots, tractor-implement automation, communication technologies for vehicles, navigation, guidance and planning, positioning systems, model-based control of mechatronic systems, drives and power systems
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-situ measurement network and perform terrestrial laser scanning, analyzing microclimate data and their relation to forest structure, and using optical satellite time series and radiative transfer models
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body organs. We are looking for a PhD student (m/f/d) to start at the TUM between now and March 2023. Your Task From animals’ circulatory system to random porous media in fuel cells, morphological