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regular activities in Greenland. Learn more at aqua.dtu.dk Technology for people DTU develops technology for people. With our international elite research and study programmes, we are helping to create a
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computer engineering, including artificial intelligence (AI), machine learning, internet of things (IoT), chip design, cybersecurity, human-computer interaction, social networks, fairness, and data ethics
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the value of the green transition. The project will involve a multi-stakeholder innovation process, utilizing a framework of multiple-loop learning to encourage farmers to reflect on their relationship with
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, for static and dynamic measurements and reliability measurements). Key Responsibilities Research & Learning: Develop expertise in GaN device physics and wide-bandgap semiconductor technology. Simulation
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enthusiastic to acquire, apply and advance their scientific skills within a dynamic international team. Our group and research- and what do we offer? The Quantum Optomechanics group at the Niels Bohr Institute
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that the candidate will learn to perform rigorous and relevant research using a combination of quantitative and qualitative research methods and extend collaborations with key academic and industrial partners at both
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within mathematics, data science, computer science, and computer engineering, including artificial intelligence (AI), machine learning, internet of things (IoT), chip design, cybersecurity, human-computer
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, and Altium; has good experience in PCB schematic and layout, and making laboratory prototypes, debugging, and testing power electronic circuits; is target-oriented, structured thinking, eager to learn
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Small case Studies of Successful Innovation Funding Methods The project will employ a combination of mainly quantitative methods, including machine learning (ML) and generative AI (GenAI) models
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with society. Whether our contributions come in the form of excellent research, innovative solutions, education or learning, we must make a positive difference to society and contribute to a sustainable