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-related materials, and materials databases would be highly advantageous. You are invited to join the Mads Clausen Institute (MCI) at the University of Southern Denmark (SDU) in Sønderborg, Denmark. The
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The Danish Institute for Advanced Study (DIAS) at the University of Southern Denmark, Odense, invites applications for one or more full-time Postdoc positions. The ’Hybrid War and Democracy
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)electrochemistry, and interest in industrial applications and cooperation to join the Mads Clausen Institute (MCI) at the University of Southern Denmark (SDU) in Sønderborg, Denmark. The position is for two
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A 2-year postdoctoral researcher position is available at the University of Southern Denmark (SDU) in the Software Engineering section of the Maersk Mc-Kinney Moller Institute (MMMI). The
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species distribution models, joint/hierarchical community models, dynamic vegetation models, or related biodiversity forecasting approaches; advanced programming skills in R and/or Python and
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chemistry. The successful candidate will be employed by Aarhus University and primarily stationed in the Research Unit of Theoretical Chemistry at the Institute of Materials Chemistry, TU Wien, in the group
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partners at UniProt, SIB Swiss Institute of Bioinformatics, and Aalborg University. The project aims to unlock decades of scattered QTL knowledge from the plant genetics literature by combining AI-assisted
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-the-art mass spectrometry techniques, as well as develop or apply coding skills (R/Python) for large-scale data analysis. Your job responsibilities As Postdoc in cardiorenal metabolism your position
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Postdoc in first-principles modelling and machine-learned force fields for correlated disorder in...
primarily stationed in the Research Unit of Theoretical Chemistry at the Institute of Materials Chemistry, TU Wien, in the group of Prof. Georg Madsen, with regular shorter research stays at Aarhus
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expertise in mouse metabolism with a willingness to learn and apply state-of-the-art mass spectrometry techniques, as well as develop or apply coding skills (R/Python) for large-scale data analysis