55 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "Ulster University" research jobs at Technical University of Munich in Germany
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) to determine greenhouse gas and pollutant emissions in cities using atmospheric measurements (MUCCnet: https://atmosphere.ei.tum.de/ ) and in-situ sensor networks in ICOS Cities project (https://www.icos-cp.eu
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for Preventing Stomach Cancer 18.03.2026 The order of the quantum world 18.03.2026 150 Years of Electrical and Computer Engineering at TUM RSS Todays events no events today. Calendar of events Find more topics on
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is expected. Background Information: Nat. Chem. 2015, 7, 105; Chem. Eur. J. 2019, 25, 4590; Angew. Chem. Int. Ed. 2019, 58, 418; Nanoscale 2021, 13, 19884. www.sengegroup.eu https://www.ias.tum.de
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, organization, compression, analysis, and visualization of georeferenced or geometric data in large scales. We put emphasis on methods of distributed computing, machine learning, image and text analysis
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and evaluation of human-machine interactions as well as the design of complex socio-technical systems. The Automated Driving Research Group addresses topics related to the interaction between users and
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related field. Strong background in robotics, estimation, control, or machine learning. Strong proficiency in Python and/or C++ and experience with ROS/ROS2. Demonstrated research experience (e.g., Master’s
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multimodal vision-language models for prompt-based 3D medical image segmentation Work with large-scale clinical CT datasets and scalable deep learning pipelines Validate models in close collaboration with
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on the nanoscale (previous works e.g.: https://www.nature.com/articles/s41563-019-0555-5). You will also supervise one PhD student who will work on a complementary topic guaranteeing quick output and an ideal
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Bewerbung, abrufbar unter https://portal.mytum.de/kompass/datenschutz/Bewerbung/. The position is suitable for disabled persons. Disabled applicants will be given preference in case of generally equivalent
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Freising, Germany Tel. +49 8161 71 3961 patrick.bienert@tum.de https://www.mls.ls.tum.de/en/cropphys/home/ www.tum.de The position is suitable for disabled persons. Disabled applicants will be given