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for human control of complex robotic systems with high levels of agency and minimal cognitive effort. Short description: This project will develop novel AI algorithms to decode human intention from
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, resulted in the EU adopting the “Action Plan for reducing incidental catches of seabirds in fishing gears”. To assess the magnitude and spatiotemporal distribution of bycatch in gillnet fisheries in Danish
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traditional embedded systems fields, such as networked embedded systems, distributed sensing systems, mobile and wearable systems, ubiquitous systems, and the (Industrial) Internet of Things. Candidates who
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of machine learning theory, algorithms and computation or in AI applications in e.g., the social, neuro, or natural sciences, are encouraged to apply. The position comes with a start package funded by
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care. While these tools promise to augment medical expertise, their integration into clinical practice poses fundamental challenges that relate to differences between expert knowledge and algorithmic
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. predation, competition, as well as behaviour and distribution at different spatial scales. Responsibilities and qualifications The professor is expected to lead the research area Fish Population Dynamics and
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of classical and quantum information • Distributed learning, classical or quantum, and the associated protocols Qualification requirements Applicants must be able to document a high degree of original
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, longest-chain and DAG-based), integrating timestamping mechanisms, and analyzing performance. The ideal candidate should have taken the distributed systems course, or prove similar knowledge, and have
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emphasis on impacts of climate and environmental factors on fish early life history, growth, reproduction, survival and distribution including invasive species. You will closely work with colleagues in
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candidates in any field of machine learning theory, algorithms and computation or in AI applications in e.g., the social, neuro, or natural sciences, are encouraged to apply. The position comes with a start