43 computational-neuroscience PhD positions at Technical University of Munich in Germany
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16.08.2023, Wissenschaftliches Personal The Chair of Computational Modeling and Simulation (CMS) at the Technical University of Munich invites applications for the position of a Research Assistant
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10.03.2025, Wissenschaftliches Personal The Professorship for Ethics of AI and Neuroscience at TUM is offering a fully funded PhD scholarship (4 years, €2,000/month) for the HARMONY project
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the courses Advanced Mathematics 1–2 and/or Statistics at the TUM Campus Straubing. Your profile: Above average master’s degree in mathematics or (theoretical) computer science with a focus on discrete
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05.06.2025, Wissenschaftliches Personal Are you looking for an opportunity to shape the future of quantum computing? With superconducting quantum computers on the verge, we aim to strengthen our
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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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and Master’s students in Informatics and Data Science. Supervise Bachelor’s and Master’s theses. We Offer Practice-oriented research projects with leading academic and industry partners (like Google
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23.07.2025, Wissenschaftliches Personal The Ecosystem Dynamics and Forest Management Group at the TUM School of Life Sciences, Technical University of Munich studies how forests change in time and space. We quantify these changes, identify their causes and describe their impacts on biodiversity...
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that are technically well-grounded and at the same time represent stakeholder preferences. The integrated Research Training Group (RTG) will provide doctoral researchers with an attractive qualification program, foster
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project funded within the DFG Priority Programme “Illuminating Gene Functions in the Human Gut Microbiome” (SPP 2474) and be involved in microbiology and molecular microbiology of the gut microbiota
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to the computational complexity of climate models, these will be replaced by physics-informed deep learning surrogates in the aforementioned model coupling. The project will initially focus on one main application