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Field
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developing state-of-the-art methods in network analysis, connectomics, and computational neuroscience. You will collaborate within a motivated, multidisciplinary team of PhD students and postdocs with
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empirical sociology and complexity approaches Learn to integrate survey data, network analysis, and agent-based modeling Develop strong skills in data analysis, modeling, and social experiments Collaborate
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coordination failures reshape decarbonization pathways. Your research will combine methods from network analysis and agent-based modelling of economic systems to trace how international material and financial
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coordination failures reshape decarbonization pathways. Your research will combine methods from network analysis and agent-based modelling of economic systems to trace how international material and financial
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network analyses experience is useful Experience in data analysis and scientific publication Ability to work in a team, good English communication skills A driver licence is useful Our offer We offer
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PhD Position on Machine Learning Detection of Positive Tipping Points in the Clean Energy Transition
sciences as well as the humanities. TPM develops robust models and designs, is internationally oriented and has an extensive network of knowledge institutions, companies, social organisations and governments
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PhD Position on Machine Learning Detection of Positive Tipping Points in the Clean Energy Transition
sciences as well as the humanities. TPM develops robust models and designs, is internationally oriented and has an extensive network of knowledge institutions, companies, social organisations and governments
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network analyses experience is useful Experience in data analysis and scientific publication Ability to work in a team, good English communication skills A driver licence is useful Our offer We offer
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development. It is one of the world's leading research institutions in its field and offers natural and social scientists from around the world an inspiring environment for excellent interdisciplinary research
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science for society. Join us in breaking new ground and writing success stories - your own and those of our university. Support us from 01.02.2026 in part-time (75 %) as a Scientific employee – Ph. D