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-classical internet Quantum embeddings for machine learning Networked quantum sensing supported by distributed classical communication Prospective applicants to this PhD proposal should have the following
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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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(density functional theory and ab-initio molecular dynamics simulations) with artificial intelligence techniques to parameterize machine learning force fields and kinetic Monte Carlo methods to model
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converging operational research, machine learning, and decision-making methodologies. The ultimate goal is to create real-time autonomous systems that are not only trustworthy but also adaptive in the face of
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Professorhip grant, which you can learn more about here: https://www.cnap.hst.aau.dk/lundbeck-professorship As a PhD fellow your tasks include: Conduct research under the supervision of senior CNAP staff members