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PhD in Quantum Computing for Power Systems Apply Vacant position PhD in Quantum Computing for Power Systems Aalborg Deadline : 30.10.2026 Department: Department of Energy Ref number: 2026/1211
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efficiency. The goal is original research for leading machine-learning, computer-vision and robotics venues. The successful candidate will be expected to conduct original, high-quality research
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closely with the reversible computing group at the University of Copenhagen, which is also an E-CoRe partner. The position connects to other ongoing projects at the Drone Center, including WildBotics
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PhD Position in Reversible Programming for Energy Efficient Cyber-Physical Systems (MSCA Doctoral...
automatically redirected to an external site after 5 seconds) Save job Click to add the job to your shortlist Send job Job Details Job Description The SDU Drone Center, part of the Maersk Mc-Kinney
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The Center for Polariton-driven Light-Matter Interactions (POLIMA) at The Mads Clausen Institute , University of Southern Denmark, is seeking a talented and highly motivated PhD student to work on
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Computing Section at Aalborg University’s Department of Computer Science. We provide an ambitious and supportive research environment focused on the design and evaluation of interactive systems that
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University of Southern Denmark (SDU) Location Odense, Fyn (DK) Salary Competitive Closing date 7 Sep 2026 View more categories View less categories Discipline Computing Job Type PhD Position Employment
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PhD Scholarships in Engineering of Quantum Light Sources and System Architecture for Photonic Qua...
engineering of system architecture for photonic quantum information technology. The position is offered within the framework of the EU Horizon Europe MSCA Doctoral Network “A Photonic Quantum Computer
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The Center for Industrial Software (CIS) at the Maersk Mc-Kinney Møller Institute , University of Southern Denmark , invites applications for a three-year PhD position in Responsible AI in Software
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degree Programming skills (Python) and experience with common machine learning platforms Experience with deep learning, computer vision, medical image analysis or unsupervised learning is an advantage