13 machining-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "https:" "https:" PhD positions in Denmark
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. This includes the use of Machine Learning (ML) and Artificial Intelligence (AI) methods. Project description The PhD project will be focused on developing, assessing, and comparing traditional and modern ML and
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organizational theory, the learning sciences, digital transformation, digital technologies, human-computer interaction, and related fields. Within the specific field, the PhD student will engage in both research
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dissemination is expected to focus on leading Human-Computer Interaction venues. For further information about the project, see: https://dff.dk/en/our-funded-projects/meet-the-researchers/research-leaders
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reduction, system identification, power electronics, model predictive control, multi-objective optimization, machine learning, renewable-energy integration, experimental testing, or hardware-in-the-loop
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are at the core of anomaly detection and despite being a well-established field of research, these are still very much open problems. To this end, we are looking for candidates interested in developing new machine
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studying how wireless sensing and AI interact in real systems. The work will be carried out in close collaboration with researchers in wireless communications, sensing, machine learning, and robotics, with
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of electrolyzer technologies, digital twins, model order reduction, system identification, power electronics, model predictive control, multi-objective optimization, machine learning, renewable-energy integration
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Engineering, Machine Learning, Applied Mathematics, or a related field. A strong academic background and interest in AI systems, embedded intelligence, edge computing, machine learning, or related areas. Strong
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, especially but not exclusively related to AI, https://digitalcurriculum.au.dk in collaboration with colleagues from CED and NAT Join as a co-teacher in a few of the departments’ workshops and teaching
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analysis, causal inference with machine learning, and deep learning for various health-related domains. The Global Pathogen Analysis Platform (GPAP) is a new international initiative to strengthen global