99 parallel-and-distributed-computing-"Meta"-"Meta"-"Meta" positions at University of Southern Denmark
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are expected to develop and sustain a research program focusing on the communication physical layers and antennas of smart devices, such as those used in IoT and edge computers, as well as signal processing and
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range of fields including applied cyber-physical systems, artificial intelligence, embedded computing, mechanical structure integrity and life assessment, heating and cooling, renewable energy systems
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to the PhD Secretariat, Faculty of Health Sciences, to be enrolled as PhD students. The PhD programme will be carried out in accordance with Faculty regulations and the Danish Ministerial Order on the PhD
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in teams of scientists and support staff with competences spanning a wide range of fields including applied cyber-physical systems, artificial intelligence, embedded computing, mechanical structure
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static and dynamic program analysis, tailored to the challenges of cross-language data communication. In particular, to systematically model and analyze cross-language communications to discover hidden
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computational resources at the University of Southern Denmark (SDU). This project offers an excellent opportunity to contribute to cutting-edge AI-based Digital Twin modeling research within an interdisciplinary
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highly motivated candidate who meets the following qualifications and characteristics: PhD (completed or soon to complete) in Software Engineering, Computer Science, Artificial Intelligence, or a closely
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. The successful candidate will work on developing new theoretical models and computational methods to investigate the fundamental limits of polariton-assisted inelastic electron tunneling in tunnel junctions made
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the applicant’s educational background and previous research experience most relevant to the offered position and the reason for applying to the PhD program. Curriculum Vitae. Master’s and bachelor’s
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) within robotics, computer science, data science, or related fields. The candidates are expected to have a profound knowledge on the majority of the following topics: Machine learning (deep neural networks