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(agent-based modeling, differential equations) or machine learning tools. Good programming skills in one of the following programming languages: R, Python, MATLAB, or similar; Excellent English language
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behaviour. In addition, you can use cost-benefit models to explore how an AMOC tipping point may influence financially optimal strategies, and/or agent-based models to explore how an AMOC tipping point will
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/ Robust) Combinatorial Optimization, Game Theory, and Network Theory, as well as Artificial Intelligence. Potentially, scenarios could be simulated using agent-based, discrete-event, or other techniques
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system dynamics, agent-based modeling, and discrete choice experiments. A passion for improving healthcare systems, particularly in oncology, and an understanding of patient preferences in the context
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with established causal models. Ultimately, you will design algorithms for causality-based analysis and counterfactual recovery of liveness violations. Information and application Are you interested in
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of topics include algorithmic fairness in network analysis, developing network embedding frameworks for real-world network datasets or AI models based on agentic LLMs for simulating real-world network data
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interfaces, and ethics and regulation. What you will be doing Inform a research agenda on the PhD topic for a timespan of four years. Develop mechanisms, interfaces, models, and systems for responsible AI
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to keep the data up-to data with very little effort. Estimate energy and land needs for the realization of the CCU potential. Develop a multi-objective optimization model for individual CCUS projects
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, ballistocardiography, and bio-radar) in combination with machine learning based algorithms for time series analysis into the whole OSA diagnosis and treatment pathway. During diagnosis unobtrusive sensors that can be
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investigate how machine-learning based algorithms can be used to personalize the user experience. The goal of this personalized user experience is to enable each individual user to discover their own