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computational models and data analysis code to process large, multimodal behavioral datasets using both traditional methods (e.g., factor analysis) as well as more modern approaches (e.g., deep learning
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I-2503 – PHD IN EXPLAINABLE AI FOR DATA-DRIVEN PHYSIOLOGICAL AND BEHAVIORAL MODELLING OF CAR DRIVERS
: · Explore methods to disentangle and integrate objective and subjective data sources to separate overlapping signal components and isolate meaningful patterns in complex datasets. · Develop AI and XAI
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methods for causal inference in observational data, is strongly preferred. Using various existing large datasets with rich information for knowledge synthetisation and triangulation over the course of the
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integrating local flexibility markets through distributed AI-based coordination, market mechanism design, and cloud-to-edge computing. It aims to develop scalable machine learning methods for coordinating grid
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integrating local flexibility markets through distributed AI-based coordination, market mechanism design, and cloud-to-edge computing. It aims to develop scalable machine learning methods for coordinating grid
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natural and artificial intelligences process information. The project is led by Heiko Schütt and will employ one PostDoc and one PhD student. About the role... You will develop new Bayesian methods
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transcripts A 3-page research proposal that presents your research project for the PhD: your research question, a short literature review, an overview over the methods and data that you aim to use The names
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pollution, and overall, the causes of tree death. The understanding and methods developed as part of the project are expected to be useful for similar studies at different sites around the world, in order to
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communications systems and methods for enhancing the physical layer security of next-generation wireless systems against threats such as jamming attacks. For details, you may refer to the following: https
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inequality, social exclusion, social participation Experience in academic research and command of quantitative and / or qualitative empirical methods; openness to mixed methods research Readiness