93 postdoc-position-in-image-coding PhD positions at Technical University of Denmark in Denmark
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PhD position focused on understanding and mitigating the environmental and health impacts of advanced membranes for water and food industries. This research sits at the cutting edge of sustainable
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at the intersection of regeneration and entrepreneurship? If so, this PhD position in Regenerative Entrepreneurship may be the right opportunity for you. The Centre for Technology Entrepreneurship (DTU Entrepreneurship
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Job Description We are looking for a motivated and creative candidate to fill a position as a PhD student as part of the MSCA Doctoral Network “SPACER” (Shaping Porous Electrode Architecture
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that will have impact on world level challenges, this PhD position is for you! The project is supervised by Alberto Santos Delgado at the Technical University of Denmark part (DTU) and co-supervised by Prof
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Job Description If you are an ambitious early-career researcher with a passion for nanofabrication and 2D materials, this PhD position offers the chance to shape new frontiers in nanofluidics
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Job Description DTU Compute and the Pioneer Centre for Artificial Intelligence are excited to offer a PhD position for a talented and motivated student to join our lab at DTU led by Theodora
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for a 3-year PhD position in Healthcare Operations with a focus on Hospital-at-home. The project is starting in January 2026 or as soon as possible thereafter. The position is part of a joint research
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-year PhD positions on privacy-preserving data sharing for future energy systems. Why this PhD at DTU? Real impact: Work in close collaboration with leading Danish partners (Energinet, Enfor, Green Power
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, this PhD position is for you. At DTU Compute, you will develop novel methods in streaming process mining and artificial intelligence to tackle real-world cyber threats, working side by side with leading
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funded PhD scholarships (3-year employment) in a vibrant interdisciplinary research environment. The positions are part of the research project “AI-driven materials optimization for light trapping in thin