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, Philosophy, Scandinavian Studies, Sinology), which must be completed by the start of the program (01.04.2026). Dissertations are generally designed as interdisciplinary projects with supervision from advisors
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Structural Health Monitoring (SHM) using smart sensor networks, and resilience-informed design platforms. Furthermore, REUNATECH promotes trans-disciplinary collaboration via multi-stakeholder platforms
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The Saxo Institute, Faculty of Humanities, University of Copenhagen (UCPH), invites applications for a PhD scholarship in the ERC Consolidator Project INNER_LEAGUE, from 1 January 2026
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The University Hospital Bonn (UKB) is a maximum care hospital with more than 1,300 beds. Our more than 9,000 employees take on tasks in research, teaching and patient care as well as in public
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Do you want to challenge prevailing narratives and contribute to new, ethical approaches to heritage management and knowledge production? This project presents an opportunity for a PhD candidate to
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related fields. • Research expertise of several months (e.g., during a Master thesis). Ideally, the experimental or theoretical methods in your command align with the research direction of the project you
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project, co-funded by the Innovation Fund Denmark and the Department of Management, Aarhus BSS, Aarhus University. Candidate profile We are seeking applicants with strong knowledge of data analytics and a
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 24 hours ago
member, apply for funding opportunities, and write manuscripts and present research at conferences. The primary role (60%) is to conduct project development, management, and implement and execute research
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-informed design platforms. Furthermore, REUNATECH promotes trans-disciplinary collaboration via multi-stakeholder platforms, bridging academia, industry, and policy. Through its ho-listic, digital, and
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for medical imaging, tailored for deep learning. The high-level goal of the project is simple: to use anatomical knowledge and existing knowledge as training data for deep neural networks (instead of manual