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-loss events undermine statistical confidence. The aim is to develop i) edge intelligence (on-turbine smart algorithms for data preprocessing), ii) resilient data movement (error-tolerant, cybersecure
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, bringing together emerging talent and senior researchers with decades of pioneering contributions. The group develops cutting-edge algorithms, frameworks, and prototype technologies that leverage high-volume
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, computer science, and statistics The objective of this PhD project is to develop machine learning algorithms that perform efficiently and coherently across both classical and quantum computing platforms. The PhD
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models to design adaptive, efficient, and intelligent algorithms for hearing assistive devices. Key objectives include improving speech perception in noisy and unpredictable environments, reducing
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. The PhD students will work on several tasks, including: development of safe data-driven control/reinforcement learning algorithms to recover parameter identifiability by exploration of different
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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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about the department at www.es.aau.dk . Description of the position The position focuses on developing next-generation learning-based decision-making and control for autonomous robots operating safely in
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algorithmic solution development. The group focuses particularly on automated decision-making in autonomous cyber-physical systems, combining mathematical optimization, machine learning, and decision theory
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on mitigating its negative impacts with limited attention given to the development of tools and processes for planning and managing waste handling in order to increase reuse and recycling rates. The purpose
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We are searching for a highly motivated PhD candidate to conduct research on the design, development, integration, and evaluation of a multimodal, Socratic AI tutor for novice programmers within