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This PhD offers a unique opportunity to work at the intersection of formal methods, control engineering, and cybersecurity within the high-stakes environment of aerospace propulsion. You will be a
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-scale vision/language/action models) can guide: World models for learning predictive representations of system dynamics Model Predictive Control (MPC) for robust decision-making under uncertainty Robotic
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and society. Our Center for Vision, Automation & Control located in Vienna invites applications for a master’s thesis. The Center for Vision, Automation & Control exploits the opportunities provided by
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development and deployment. Ability to assess and mitigate common access control attacks and implement robust security controls across web platforms. Proven hands-on experience administering and integrating
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. Over the past decade, Sorin Olaru and collaborators developed MPC-based congestion management and distributed control tools that account for storage and curtailment [1, 2, 3]. These works motivate
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fully declarative, version-controlled infrastructure and software delivery. Developing and maintaining robust CI/CD pipelines using modern DevOps toolchains Engineering secure platforms, implementing
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involves designing, commissioning, and operating a fully automated fermenter system to support advanced bio-manufacturing, including the development of robust protocols for process control, monitoring, and
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— including AMRs/AGVs and exoskeletons. Proficiency in C, C++, and Python, with experience writing robust, task-specific algorithms for perception, localization, mapping, navigation, and control. Solid
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involves designing, commissioning, and operating a fully automated fermenter system to support advanced bio-manufacturing, including the development of robust protocols for process control, monitoring, and
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uploaded using the dedicated electronic form. helpdesk: petra.koudelova@fsv.cvut.cz Physics-guided learning for machine control Description: Robust machine control assumes modeling of robot-environment