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, Denmark [map ] Subject Areas: Nonparametric estimation, Machine learning methods in econometrics and time series analysis, Statistics for high-dimensional data, Stochastic volatility models Appl Deadline
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research in Time Series Analysis and Econometrics with focus on one or more of the following key research areas: Nonparametric estimation. Machine learning methods in econometrics and time series analysis
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advanced modelling, data analysis, and algorithmic development. Your tasks will support our core research focus of mathematical and computational approaches to design and implement solution algorithms, with
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towards a more sustainable built environment. The announced position is part of this new research program: Civil Engineering and the Green Transition in the Built Environment (CEBE), and the successful
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PhD Stipend/Integrated Stipend in representation, compression, learning, and inference for classical and quantum data. At the Technical Faculty of IT and Design, Department of Computer Science, one
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student and group supervision using PBL methods, is expected. In addition, experience with formulating research ideas and contributing to grant proposal writing will be considered an advantage. • A
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to developing methods and tools that support a cost-effective, flexible and sustainable integration of cooling in future energy systems. Your work will be structured around two strongly interconnected research
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quantitative research methods, or the ability to combine different methodological approaches in interdisciplinary research, will be considered an advantage. Experience with research project development
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The Technical Faculty of IT and Design, Department of Computer Science, Section for Copenhagen, Human Augmentation and Collaboration research group The Department of Computer
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-experimental data from five countries. Methodologically, the project designs and implements survey experiments and other causal inference methods (e.g. difference-in-differences and synthetic control). Your