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Field
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technology. What you will do As part of an internship, we offer you the opportunity to deepen your interest and knowledge in the field of machining. You will learn how to use CNC machine tools and manufacture
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the Cluster of Excellence (Machine Learning for Science), the ERC Starting Grant ArtDisQ and the University of Tübingen. Salary will be determined according to the German collective wage agreement in public
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); Doctorate in Physics, Computer Science or related fields (for Post-Docs). The positions are funded via the Cluster of Excellence (Machine Learning for Science), the ERC Starting Grant ArtDisQ and the
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, Rehabilitation, Biostatistics, Python, R, SQL, Machine Learning, Real-World Data, TUM Hospital The position is suitable for disabled persons. Disabled applicants will be given preference in case of generally
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optical communication networks and systems, as well as machine learning, computer vision and compressing digital videos. The Sustainable and Modular Networks (SMN) working group operates in an international
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the use of machine learning methods to process complex data sets. The focus is on techniques such as ultrasound, radar, computed tomography, acoustic emission analysis, and infrared thermography
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. Strong coding skills for programming neural networks, machine learning and machine learning software frameworks (e.g. PyTorch or Jax) is a must. The ability for creative and analytical thinking across
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. The Leibniz-LSB@TUM comprises a unique and world-leading research profile at the interface of Food Chemistry and Biology, Chemosensors and Technology, and Bioinformatics and Machine Learning. Leibniz-LSB@TUM’s
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of reaching climate neutrality by 2050. By leveraging characterisation, multiscale modelling, machine learning, and numerical optimisation, the project seeks to craft a magnetic multiscale modelling suite
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ENGAGE Network at TUM and GIM Robotics. About the ENGAGE Network Mobile working machines (MWM) are critical to industries like construction, mining, and agriculture, and key to Europe’s sustainability and