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framework for AI in gynecological oncology. We integrate symbolic knowledge representation (Ontologies/Knowledge Graphs) with Retrieval-Augmented Generation (RAG) and Large Language Models (LLMs) to create
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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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quantitative live-cell imaging to probe and model these processes. By combining stem cell biology with cutting-edge microscopy and physical concepts, we aim to establish a predictive framework for tissue self
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learning, safety-critical control, probabilistic modeling, verification, or optimization; Excellent communication skills in English and the ability to work both independently and collaboratively in
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of stem-cell derived models, these platforms open new avenues to systematically explore tissue self-organization and disease mechanisms. The group of Prof. Bausch is establishing an automated cell culture
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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
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Models, LLMs, etc. PhD and PostDoc Positions in Visual Computing & AI The Visual Computing & Artificial Intelligence Group at the Technical University of Munich is looking for highly motivated PhD students
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correction and fault-tolerance - Quantum optics of trapped ions and Rydberg atom arrays - Numerical tensor network techniques - Topological order and (de)confinement in string-net models - Quantum field theory
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, depending on the geographical and economic context. It will include a deep dive on the potential of Ukraine to become a green hydrogen hub, leveraging geo-spatial energy models run by project partners. As
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verified with applications from geodynamics. For more information consider the job description here . Tasks Tasks in the project include the efficient implementation of new models, methods, and algorithms