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Field
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The successful candidate will develop generative machine-learning methods for amorphous molecular thin films — the supramolecular structures that govern the performance of organic-electronic materials
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31.07.2026, Academic staff We are seeking a researcher in Scientific Machine Learning (SciML) to join the project "Data science at scale" at the Technical University of Munich, Germany. Ideal
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: Design, implement and characterize innovative sensing systems based on different sensing principles such as ultrasonic, optical and chemical sensors. Investigate sensor behavior under varying environmental
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In this position, you will join our Simulation and Data Lab for AI and Machine Learning for Remote Sensing . The lab advances interdisciplinary research and operational services by combining
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Munich form one of Europe's leading centers for biomedical imaging and sensing innovation. Our mission is to create transformative technologies that reveal previously inaccessible biological information
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Max-Planck-Institut für Kohlenforschung, Mülheim an der Ruhr | M lheim an der Ruhr, Nordrhein Westfalen | Germany | 19 days ago
combines experiments, quantum chemistry, and spectroscopy to study reaction mechanisms and to discover how solvation and catalyst design affect the rate and selectivity. Current projects focus on developing
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experimental and testing protocols Investigating functional additives to improve anode performance and stability Developing suitable current-collector concepts for alkaline battery operation Designing and
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Essential qualifications A master's degree in Physics, Electrical Engineering, Chemistry, or a related field and the ability to design, execute, and troubleshoot complex experimental research. What we offer A
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Learning at TUM works on machine learning, artificial intelligence, and information processing, with a current focus on foundation models, data-centric research, and applications to scientific and medical
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will strengthen the data science and machine learning activities of IAS-9 by developing core AI methods with applications to electron microscopy and materials discovery. You will work in a team of data