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impact analysis, Resource allocation, growth and welfare evaluation, Technology diffusion and firm level innovation. leading to an internationally competitive PhD degree and internationally peer-reviewed
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with experience in causal inference using panel data (e.g., Difference-in-differences) solid knowledge of Stata, R and/or Python for conducting econometric analysis previous knowledge of conducting
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learning tools for the efficient analysis of the experimental data. For more information, visit our web page www.soft-matter.uni-tuebingen.de We are looking for a motivated PhD student to contribute
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impact. Tasks: Research Objectives: Definition of a suitable interface region based on the results from other IRP. Numerical analysis of the emission propagation in the near field of the re-entering
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methods for dealing with time-dependent and/or unmeasured confounding. We seek an excellent, open-minded, and team-spirited PhD candidate who is interested in statistical aspects of secondary data analysis
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and Data Science (MIDS) at the KU Eichstätt-Ingolstadt. The research group works at the intersection of analysis, modeling and simulation. The advertised position is partly funded by the German Research
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are looking for talented people to join us. Your responsibilities include: MI Project IE2501 “Safe Hydrogen Networks: ML-Supported Safety Analysis and Optimized Sensor Placement” Research in the field of safety
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, agricultural sciences with a focus in economics, or related disciplines strong analytical and methodological skills with a focus on quantitative data analysis (e.g., econometrics, statistics, machine learning) a
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properties of novel two-dimensional materials combined with quantum dot nanostructures: spectroscopic investigations of two-dimensional semiconductors, measurements and analysis using microscopy and time
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analytical and methodological skills with a focus on quantitative data analysis (e.g., econometrics, statistics, machine learning) a high motivation and the ability to work independently with a strong team