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. will be developing efficient and reliable algorithms that arise in the context of topological data analysis and rendering for the visualization of large amounts of data. Close cooperation with other
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safety. You will work on developing control algorithms all the way to performance assessment in test vehicles. The project combines theoretical aspects of control algorithms, experimental design, and
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the intersection of control theory, robotics, artificial intelligence, and signal processing, and is a key enabler of future intelligent infrastructure.This project will focus on the development of novel control
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into how algorithmic systems influence the circulation of information and disinformation across digital platforms, and how such processes affect perceptions of credibility, truth, and democratic
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, localization, and sensing, with a focus on developing next-generation multiple-antenna systems while optimizing overall system performance. As a doctoral student, you devote most of your time to doctoral studies
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algorithms to detect complex structural variants in humans using long DNA sequencing reads. A structural variant (SV) is a large-scale alteration in the genome that involves rearranged, deleted, or inserted
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theoretical research, algorithm design, and the development of software tools that demonstrate the applicability of the new methods. Research environment The positions are hosted by the Department
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the theory of optimization algorithms and high-dimensional statistics to address some of the most fundamental questions in ML such as the behavior of neural networks. The environment of this project is highly
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modular, scalable, and transparent control algorithms suitable for real-time implementation across different vehicle platforms. - Contribute to theoretical developments in stochastic model predictive
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and empirically oriented, focusing on how political ideas, actors, and conflicts are shaped and mediated through digital platforms. Central themes may include, for example, algorithmic influence