297 data "https:" "https:" "https:" "https:" "Dr" "L2CM" "L2CM" Postdoctoral positions in Denmark
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University with related departments. Contact information For further information, please contact Prof Kim Daasbjerg at +45 23 48 52 49 or kdaa@chem.au.dk or alternatively Associate Professor Behzad Partoon
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. Key activities include analysis of clinical and patient-reported outcome data, coordination of implementation studies in collaboration with ENT clinics, dissemination of results through peer-reviewed
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information For further information, please contact: Professor Torben Heick Jensen, thj@mbg.au.dk, phone +45 60202705 Application procedure Shortlisting is used. This means that after the deadline
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information For further information, please contact: Professor Torben Heick Jensen, thj@mbg.au.dk, phone +45 60202705 Application procedure Shortlisting is used. This means that after the deadline
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execute MR experiments using hyperpolarized 13C tracers in collaboration with project partners Develop robust experimental procedures and protocols to ensure reproducibility Contribute to data analysis and
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University with related departments. Contact information For further information, please contact Prof Kim Daasbjerg at +45 23 48 52 49 or kdaa@chem.au.dk or alternatively Associate Professor Behzad Partoon
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systems. Further information on the Department is linked at https://www.science.ku.dk/english/about-the-faculty/organisation/ . Inquiries about the position can be made to Assoc. Prof. Leonardo Midolo
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, which is a collaboration between the Department of Business Development and Technology and the Department of Digital Design and Information Studies. The project ‘Practice Resonant AI Ethics for the Public
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inorganic syntheses Develop and optimize electrochemical experiments and measurements Characterize materials and compounds using standard analytical techniques Analyse data and document results Collaborate
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at the Department of Electrical and Computer Engineering, Aarhus University, where we are advancing communication-efficient and distributed foundation model inference across the computing continuum