61 phd-agent-based-modelling Postdoctoral positions at Technical University of Munich in Germany
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the understanding of the trade-offs between production, mitigation and conservation in livestock-based systems, and to identify innovative mechanisms for landscape-level management. Our group combines empirical work
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for safety-critical bilateral teleoperation. The research will leverage a combination of passivity-based control methods and machine learning techniques to enable reliable and robust teleoperation in uncertain
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focus on deep networks for solving inverse problems, learning robust models from few and noisy samples, and DNA data storage. The position is in the area of machine learning, with a focus on deep learning
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, or electrochemical CO2 reduction. To do so, the preparation of novel catalyst materials is of pressing concern. You will continue our research line around the preparation of novel catalysts based on mixed metal alloys
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will develop into acute or chronic infection. Your expertise - PhD in life sciences, preferably (liver) immunology and/or viral hepatitis. - Experience in high-dimensional flow cytometry for phenotyping
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, and high-performance computing. It aims to improve the performance of the matrix-free finite-element-based framework HyTeG, in particular by techniques for data reduction through surrogate operators
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cooperation with the other scientists is a prerequisite. Your profile: You have a PhD, work experience and several publications in the field of solid oxide cells. In addition, fluent written and spoken English
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consortium-based tasks related to the 6G-Life project. Additionally, the methods and findings developed throughout the PhD track will be scalable and applicable to other research projects in MIRMI
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). Employment Conditions • Start date: Flexible, from January 2026 onward • Salary: Based on the German public sector pay scale TV-L E13, commensurate with experience and qualifications. • Generous funding
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machine learning-based systems to integrate more renewable energy into our energy systems and make energy use more efficient. We develop new optimization methods, machine learning algorithms, and