67 phd-studenship-in-computer-vision-and-machine-learning PhD positions at Technical University of Munich
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systems on different temporal and spatial scales. For our Research Group Applied Optimization we are looking for a PhD student: New Deep Learning - based Framework for Energy Modelling: Combination
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systems on different temporal and spatial scales. For our Research Group Applied Optimization we are looking for a Research Associate / PhD: Physics-informed deep learning for PDE-constrained optimization
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control software and machine learning expert. How you will support us: ▪ You will take on responsibilities in the field of control and operation of high-coherence superconducting quantum circuits, with a
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computer vision in dusty conditions by incorporating hyperspectral cameras. In addition, assisting in project applications and general development duties of the Chair. The position is available from
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for three PhD positions to be filled on August 1st 2025 to enlarge our research team working on NLP for medical applications. PhD Positions in NLP for Medical Applications The Chair of Software Engineering
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. However, how insects perceive, discriminate, and process the biological information encoded in CHC profiles remains poorly understood. PhD Position: The PhD candidate will investigate the chemoreception
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PhD position in interpretable machine learning for dementia prediction. The project focuses on developing interpretable deep learning models for dementia prediction using multi-modal data, including MRI
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06.06.2025, Wissenschaftliches Personal We are looking for 1 PhD Position in Robotics and AI to work at the Technical University of Munich (Garching Campus) within this multi-disciplinary cohort. We
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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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, 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