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, Machine Learning, Hyperspectral Cameras • Professional proficiency in written and spoken English Application process Send your application in English by email to amx@wzw.tum.de with the title “Research
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, ideally in Python, with demonstrated experience in applying them in complex research or development projects Basic knowledge in Machine Learning, ideally supported by initial hands-on experience Experience
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subjects, high interdisciplinary desire to learn, and willingness to cooperate, openness for internationalization and diversity, very good verbal and written English communication skills (good command
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is available from 01.11.2025. About us The Chair of Agrimechatronics (Prof. Oksanen) studies especially Intelligent Machines for Agriculture. The research themes include topics like tractors and other
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knowledge in food chemistry and superior interest in food systems biology, food-related research • Keen interest in learning and applying experimental biophysical techniques, in particular AFM (essential
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with chemoreception and sensory biological techniques (SSR, GC-EAD, EAG). •Experience in analytical chemistry (GC-FID, GC-MS). •Experience in or willingness to learn statistical data analyses, data
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are therefore ex-pressly welcomed <>< b=""><> Please send your application with relevant documents by August 28 2025 at the latest to: Technical University of Munich Chair of Ecosystem Dynamics and Forest
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private machine learning: Differential privacy (DP) is the gold-standard for privacy protection, but deep learning models trained with DP suffer from privacy-utility trade-offs. You will develop novel model
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diagnosis, and knowledge of the operation of helicopter systems. • Confident handling of Python and common data science tools. • Knowledge of high-performance computing and machine learning. • Fluency in
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or for multiobjective optimization problems. Implement the developed algorithms (e.g., in Python) and evaluate their practical performance on artificial and/or real-world data. Teach tutorials (in English) for