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on real-life data from the maritime industry. As part of the PhD, you will be following advanced courses to extend your skills, implement and test algorithms, and learn to write scientific papers. As part
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pruning), carbon-aware computing, minimizing algorithmic complexity, maintenance requirements, mapping energy efficiency and related aspects using KPI (key performance indicators) with respect to ESG
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correction and/or mitigation. Knowledge about networking protocols and distributed algorithms. Experience in programming, e.g., in C++, Python or Matlab. Experience with quantum simulators, such as NetSquid
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Job Description Are you interested in working at the intersection of optimal control, AI algorithms, and game theory, on problems that matter for real-world critical infrastructure? This PhD
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deliver a theoretical, algorithmic, and real-time implementation framework for on-the-fly autonomy in crowds. The resulting methods will (i) adapt to unpredictable human interactions that introduce high
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algorithmic management in transforming organizational structures and labor relations The societal, political, and geopolitical implications of AI and related technologies The governance and regulation of AI
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correction and/or mitigation. Knowledge about networking protocols and distributed algorithms. Experience in programming, e.g., in C++, Python or Matlab. Experience with quantum simulators, such as NetSquid
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, algorithmic, and real-time implementation framework for on-the-fly autonomy in crowds. The resulting methods will (i) adapt to unpredictable human interactions that introduce high levels of uncertainty, (ii
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some of the following skills: Localization and sensor fusion: Solid understanding of localization techniques and sensor integration. Experience with SLAM algorithms (vision-, acoustic-, or inertial-based
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sensor integration. Experience with SLAM algorithms (vision-, acoustic-, or inertial-based), state estimation (e.g. Kalman filtering, pose graph optimization), or collaborative positioning is highly valued