117 master-"https:"-"https:"-"https:"-"https:"-"IFM"-"IFM"-"IFM" Postdoctoral positions in Denmark
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methods (e.g. workshops, digital sprints), and ethnographic fieldwork. You will be breaking new ground within STS and Valuation Studies in a larger research team led by Principal Investigator, Professor
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. Your primary responsibilities include: Investigating optimal power architectures for an 800 V bus in next-generation AI infrastructure. Developing high-efficiency, high-density power converters
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disposal. The department has overall responsibility for the Master's degree programs in medicine and in molecular medicine. At the department we are approx. 425 academic employees and the same number of PhD
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. The postdoc is expected to be willing and able to contribute to the Centre for Journalism achieving two strategic goals: 1) To produce original research of high international quality, and 2) to exchange
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. The project includes collaboration with leading international experts in proteomics and dermatology and provides access to modern research facilities. The principal investigator is Assistant Professor Xiang
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. The project includes collaboration with leading international experts in proteomics and dermatology and provides access to modern research facilities. The principal investigator is Assistant Professor Xiang
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academic qualifications at master's degree level. Appointment as postdoc requires academic qualifications at PhD level. Who we are The research group is recognized internationally as a strong research group
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will lead a research project with the aim to understand the functional role and disease mechanisms of protein complexes associated with primary cilia and centrosomes. Cilia are antenna-like organelles
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particular focus on Child-Computer interaction, AI literacy, and computational empowerment. The main tasks will consist of conducting research on participatory approaches to the design and study of AI literacy
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main areas of work: Exploration of heterogeneity in GDM risk and GDM subtypes and application of these insights to develop a GDM risk prediction model, based on data from The Danish Blood Donor Study