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19.07.2022, Academic staff The Machine Learning and Information Processing group at TUM works in the intersection of machine learning and signal/information processing with a current focus on deep
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project, we are looking for a strong candidate to contribute to the development of quantum algorithms and applications, focusing on quantum walks and quantum machine learning on graph structures. Your
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Imaging, Machine Learning, or a related field • Demonstrated research experience in generative models for medical imaging (e.g., diffusion models, VAEs, GANs) • Publications in high-ranking journals and
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multimodal vision-language models for prompt-based 3D medical image segmentation Work with large-scale clinical CT datasets and scalable deep learning pipelines Validate models in close collaboration with
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to joint research activities, publications, and surveys. Requirements PhD degree (or near completion) in robotics, control, machine learning, or a related field; Strong publication record demonstrating
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involve the integration of: Advanced motion planning and control algorithms Multi-modal perception techniques (e.g., vision, tactile, force) Machine learning models for physical behavior prediction and
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training machine learning models (ideally with a focus on LLM), high-performance computing, data management, and software architecture Strong Python programming skills and familiarity with machine learning
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, imaging). • Solid foundations in signal processing and statistics. • Experience with machine learning for regression (e.g., tree-based methods, neural networks) • Hands-on experimental skills: ability and
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management skills • Experience with qualitative or mixed-methods research • Familiarity with AI, machine learning, neurotechnology, or robotics research contexts • Interest in science policy, governance
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-XRF, Raman, FTIR in reflection mode) to enable multimodal data fusion and automated material characterization. • Apply and further develop machine-learning and statistical models (e.g. PCA, SAM