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Moderna. PRAYER sets out to conduct the first large-scale investigation of this unique corpus by introducing a new approach – network philology – that studies all aspects of vernacular prayer books in
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observability, potentially integrating physics-aware constraints and generative modelling approaches. Both tracks interact closely to create a data–model feedback loop, enabling systematic analysis of how
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) are facing a critical methodological juncture. While commercial AI tools like ChatGPT offer powerful capabilities for text analysis and coding, they act as black boxes that obscure how data is processed, pose
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forecasting capacity. What you’ll do Together with the PI, you will provide scientific leadership for QUASI’s observational backbone and take responsibility for the design, operation and analysis of the multi
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, from fellow academics to patients. You have experience with analysis of sensor data. You have an affinity for patient care and are able to communicate with patients. You have a good command of written
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to ESA’s strategy; a wide network of relationships and collaboration with top academics, industry and research centres; the opportunity to contribute to the Φ-lab strategy and activities. As an internal
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), and physiological parameters in the study of animal behaviour; a strong background in data analysis using R, preferably experience with Bayesian statistics and social network analysis; lab experience
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with design partner Studio Bertels to translate your findings into public showcases and policy tools. We are looking for a researcher who is comfortable with advanced data analysis and eager to apply
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networks, risk analysis or uncertainty quantification (preferred). Knowledge of data science in general as well as practical experience with conducting data science analyses with good programming skills
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and analysis pipelines are underway. Working closely with the principal investigator and collaborators, you will complete the main analyses, stress-test robustness, and contribute to the writing