60 parallel-computing-numerical-methods PhD positions at Technical University of Munich
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numerous severe human diseases. Despite these key roles in biology and medicine, cellular mechanisms of membrane protein biogenesis and control remain ill-defined. The project will investigate biological
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for Preventing Stomach Cancer 18.03.2026 The order of the quantum world 18.03.2026 150 Years of Electrical and Computer Engineering at TUM RSS Todays events no events today. Calendar of events Find more topics on
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, including droughts, fires, and deforestation, as well as ecosystem resilience and tipping points. Key Responsibilities The successful PhD candidate will: Develop and apply machine learning methods (e.g. CNNs
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12.01.2026, Academic staff The Professorship of Machine Learning at the Department of Computer Engineering at TUM has an open position for a doctoral researcher (TV-L E13 100%; initial contract 1.5
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information-theoretic approach that embeds security directly into the physical transmission layer, ensuring resilience against future attack methods, e.g., by quantum computers. We are seeking a highly
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, leveraging a principled combination of passivity-based control methods, machine learning, and human-in-the-loop systems to enable robust teleoperation in uncertain and delayed communication environments. Key
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tailored computational methods are needed. This project aims at combining probabilistic machine learning methods with prior knowledge in the form of graphs to analyze and predict food-effector systems. Key
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societal aspects (ELSA) of NeuroAI in the life sciences and biomedicine. The project focuses on (i) neu-romorphic computing inspired by the human brain and (ii) AI-enabled neurotechnologies for clinical and
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, which provide bioengineering solutions to urgent societal needs. IBMI scientists develop next-generation imaging and sensing methods to measure previously inaccessible properties of living systems, hence
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molecular level. To yield new insights into food-effector systems, sophisticated and tailored computational methods are needed. This project aims at leveraging graph-theoretic approaches to analyze and