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techniques including graph neural networks, Bayesian neural networks, conformal prediction intervals and generative AI for synthetic data generation. You will also develop frameworks for uncertainty
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networks, Bayesian neural networks, conformal prediction intervals and generative AI for synthetic data generation. You will also develop frameworks for uncertainty quantification in forecasting and
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, methodologies, and information derived from Bayesian modeling, data science, cognitive science, and risk analysis. Its primary objective is to create advanced forecasting models, generate meaningful indicators
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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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://www.universiteitleiden.nl/en/staffmembers/laura-heitman#tab-1 at Leiden University! What you will do Project objectives are: Develop expression and purification methodologies for GPCRs Develop and optimize affinity selection
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objective is to investigate how new technologies challenge moral values and ontological concepts (like “nature”, “human being” and “community”), and how these challenges necessitate a revision of these
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purification, but undesirable when cultural-heritage objects fade or when pharmaceuticals or protective coatings degrade. Understanding the chemistry of light-induced degradation (LID) is essential, yet highly
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, considering algorithmic challenges such as multiple objectives, the robustness of designs and the transparency of the design recommendation process. The position is offered in the context of the Mobility
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competence in three-dimensional Lagrangian Particle Tracking, Object-Aware Shake-the-Box algorithms and helium-filled soap bubbles seeding for large-scale 3D-LPT experiments. You are familiar with LaVision
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the broader research activities of the Data Science Center of Excellence of the Ministry of Defence. The central objective of this research is to investigate how data-driven and predictive models can be