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work tasks The research assistant working as Chapter Scientist (SC) for the IPPC will work for the Report AR7 and must provide technical support to chapter 4 on Sustainable Development and Mitigation
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at the intersection of AI, RF, and wireless communication. Your main tasks include developing machine-learning methods for wireless interference detection, mitigation, edge intelligence, and applying AI to optimize RF
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(https://www.classique.aau.dk). CLASSIQUE will address a suite of fresh research challenges defined by the intersection of digital applications that have real-time requirements and quantum resources
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to evolve classical communication networks to support both traditional data and the unique requirements of quantum information systems (https://www.classique.aau.dk). CLASSIQUE will address a suite of
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on development of wave energy and offshore wind. Most of our research is focused around work in our wave flume and basin. Further description of the group may be found here: https://vbn.aau.dk/en/organisations
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Andres Masegosa (arma@cs.aau.dk), Department of Computer Science. (please see: https://andresmasegosa.github.io/ . The project’s domain PI is Professor Jamal Jokar Arsanjani (jja@plan.aau.dk), Department
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, non-communicable diseases, multi- and co-morbidity and rehabilitation) that shape our vision for sustainable and healthy and sustainable future. We educate bachelors and masters of science within
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. The stipend is within the Data Engineering, Science, and Systems (DESS) research group and supervised by Professor Torben Bach Pedersen. Within Digital Energy, DESS has developed the award-winning FlexOffer
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. The candidate should demonstrate research on emerging technologies for collaborative learning, including areas such as video-based competence development, digital mediation of learning processes, and the use
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development of inclusive practices in educational and welfare contexts. Practice-oriented and collaborative research methodologies, that support innovation and intervention in educational psychology practice