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Field
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data Development of algorithms for infection and evaluation of infection hotspots in the plant population Coordination of the scientific interface to the project partners with regard to entomological
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-learning algorithms Versatile data-science knowledge, including image and DNA sequences processing Programming skills in Python or other modern programming languages supporting AI and bioinformatics
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-sampling data. Furthermore, the position holder will play a central role in creating high-quality training datasets (seagrass maps) to support artificial intelligence (AI) algorithms used in related projects
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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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near-real-time forecast system for the Baltic Sea Generate high-resolution daily surface salinity maps for the Baltic Sea and validate them with available observational datasets Develop algorithms and
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data analysis and develop sophisticated mathematical models for simulating power system behaviors under various scenarios. Development and Testing: Design and develop control algorithms to enhance grid
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compressed sensing) 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
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to develop a 3D-generative algorithm for pharmaceutical drug design by using or combining novel machine learning approaches? How would you integrate machine learning, physics-based methods in an early-stage
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research studies for automated image analysis. In particular, you will: Plan, develop, and implement AI/ML algorithms for pathology image analysis. Integrate multi-modal data (e.g., genomics, clinical data
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, and characterization Develop gate implementations, benchmarking and algorithms Work on the interdisciplinary challenges in systems engineering Install and improve experimental setups and fabrication