171 development-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"https:" positions in Denmark
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cardiometabolic disease. Together, our research programme combines fundamental discovery with early-phase clinical translation to develop innovative immunotherapies capable of achieving long-term control or cure
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contribute actively to the department's research and teaching activities. You are expected to conduct research at a high international level and to develop an independent academic profile through both
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responsibility of the position will be to lead and develop a research group in clinical AI with special focus on leveraging multimodal clinical data for clinical decision support. You will work in close
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markets are governed. To test and develop this theory, the postdoctoral researcher will conduct sector case studies in different countries focusing both on the link between deviant business strategies and
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colleague, you will join a dynamic research environment and are expected to contribute actively to the continued development of the group's research on technology diffusion and digital transformation. You are
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, you will work at the intersection of polymer processing, materials science and Machine Learning to develop dynamic recipes for sustainable plastics. In a typical plastics production line, several types
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knowledge and developing applied solutions to major public health challenges. Our research spans theoretical, basic, and applied sciences, with the shared ambition to generate impactful knowledge and
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environment and to the faculty’s overall research strategy. You will contribute to the development of NCRR and the Department of Public Health both individually and in collaboration with others via your
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to collaborate across research groups and career stages, contribute to shared research and teaching activities, and develop an independent academic profile. As a member of the section, you will be part of both a
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postdoctoral researcher to join an interdisciplinary team developing deep learning models for antimicrobial resistance (AMR) detection directly from MALDI-TOF mass spectrometry data. The project is funded