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and regulatory context. Objectives Develop an agent-based modelling and stakeholder analysis toolkit to capture the perspectives, needs, and regulatory constraints of main stakeholders. Design modular
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creative – You bring substantial knowledge of statistical (e.g. Bayesian) methods, strong analytical skills, and creativity. Programming skills – You are proficient in Python and/or Matlab. Research
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for differentiating effectful programs such as gradient estimation of probabilistic programs, implicit function differentiation, compositional Bayesian inference techniques); analyzing what is required (e.g., choice
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modelling approach, and dynamic Bayesian Networks would be advantageous. Willingness to conduct research in a multi-national project team. Funding requirements: You cannot have resided in The Netherlands in
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. Besides this, you will work on scene understanding using RGB and possibly thermal and radar images, including based on object detection and image segmentation, and collaborate effectively with other
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will explore advanced THz front-end architectures and evaluate their applicability in real-world scenarios. Key objectives include: Exploring use cases and front-end architectures in the 300–500 GHz
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at the “small” scale of atoms and molecules. Imagine extending effects like quantum superposition and entanglement to “large” objects that we usually think of as classical particles. This is exactly what you will
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superposition and entanglement to “large” objects that we usually think of as classical particles. This is exactly what you will do at TU Delft. As a PhD student in our teams, you will investigate how
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function differentiation, compositional Bayesian inference techniques); analyzing what is required (e.g., choice of data structures, static analyses and compiler optimizations, parallelism and concurrency
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within FlexMobility will focus on the underlaying assignment and routing algorithms for real-time operation of the vehicle fleet and the multi-objective design of the mixed transporation network. Our key