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particular the development of generative AI technologies such as diffusion models, flow matching, generative transformers, or related architectures. The position is highly methodological and focuses
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, molecular biology, or a related discipline a strong conceptual and experimental background in immunology substantial hands-on experience with in vivo mouse models extensive experience with flow cytometry and
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improve high-throughput experimental workflows including closed-loop thin-film optimization Apply AI and Machine Learning for data analysis and modelling Develop, improve and implement HW/SW concepts and
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experimental workflows including closed-loop thin-film optimization Apply AI and Machine Learning for data analysis and modelling Develop, improve and implement HW/SW concepts and components to automate
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Your position We combine mouse tumour models, immunology, molecular biology, flow cytometry, imaging and single-cell approaches to investigate how neurons, immune cells and stromal cells communicate
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communities as a model system. Main duties and responsibilities Anaerobic digestion communities are among the best-characterized and most ecologically important microbial ecosystems. Composed of diverse
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and how neuro-immune communication contributes to inflammatory or tumour-associated disease states. Approaches include neuronal tracing, in vivo disease models, genetic and viral manipulation
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the molecular mechanisms of prostate cancer progression and therapeutic resistance. The group combines functional genomics, translational pathology, and cutting-edge experimental models to drive discoveries from
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to answer: How temporal and structural sparsity can be incorporated into the 3D dynamics reconstruction model? How sparse can a measurement be and still capture a high-resolution dynamic event? How do
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to answer: How temporal and structural sparsity can be incorporated into the 3D dynamics reconstruction model? How sparse can a measurement be and still capture a high-resolution dynamic event? How do