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Field
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with reinforcement learning algorithms is a strong plus. TU Delft (Delft University of Technology) Delft University of Technology is built on strong foundations. As creators of the world-famous Dutch
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System applications, system/segment/payload system architectures and performance, signal-in-space and signal processing, GNSS receivers, algorithms, OD&TS, formation-flying and radio frequency/optical
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sufficiently “compact” (i.e. algorithmically small and computationally efficient) to enable incorporation in integrated PED models. The development of these compact models will involve collaboration with several
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Postdoc Impact of Computational Infrastructures on Public Institutions and Administration of Justice
of “clouds”. Popular discussions revolve around the topics of data protection, algorithmic regulation, and asymmetric ‘technological dependencies’ that raise concerns around monopolies and “digital sovereignty
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Dutch and English. Affinity or experience with innovation projects involving partners from practice. Willingness or experience in programming heuristics and algorithms. Motivation to produce academically
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control with teleoperated human inputs? Change: Develop novel algorithms and interfaces for teaching robots in shared control with human operators. Impact: Provide a seamless interface for humans to teach
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software development (e.g., treatment planning tools, imaging algorithms, AI-based applications). Excellent collaboration and communication skills. Fluency in English (spoken and written); Dutch language
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, and translational research. Proven analytical skills and experience in experimental research. Experience in software development (e.g., treatment planning tools, imaging algorithms, AI-based
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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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across domains. The research unit Intelligent Systems (IS) in Computer Science is focused on the development of Data Science, Pattern Recognition and Machine Learning algorithms for interdisciplinary data