50 linked-data-"https:"-"https:"-"https:"-"https:"-"https:" Postdoctoral positions in Denmark
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to experimentally derived disorder models and data from methods such as total scattering/pair distribution function analysis, diffuse scattering, diffraction, solid-state NMR and electron microscopy. Work closely
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responsibilities are assigned. The position is linked to the Nordic Baltic research project GAIYA: Generative AI in Education for Young Adults (2026–2030), funded by NordForsk. As postdoctoral researcher, you will
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Department of Food Science's controlled-environment testing activities in Work Package 5 of the EVOLVE project. The work will generate biological evidence linking extracellular vesicle (EV) treatments to plant
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innovative ways to utilize the many data sources already available in PREDICT, including registry data, genomics, microbiomics, metabolomics and epigenetics. The postdoc fellow will join a multidisciplinary
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are software representations of physical assets, processes, or systems. They leverage real-time data to mirror the behaviour and characteristics of their physical counterparts, enabling predictive maintenance
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employment is Aarhus University with related departments. Contact information For further information, please contact Prof. Klaus Koren, [email protected] Deadline Applications must be received no later
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well as develop or apply coding skills (R/Python) for large-scale data analysis. Your job responsibilities As Postdoc in cardiorenal metabolism your position is primarily research-based but may also involve
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thereafter. Explaining complex AI models is a key challenge for ethically responsible AI. Explainable AI (XAI) research aims to provide relevant information to assist developers and users in analyzing AI
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with related departments. Contact information For further information, please contact: Professor Troels Skrydstrup, +45 28 99 21 32, [email protected]. Application procedure Shortlisting is used. This means
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) to study atomic structures of optically excited small unit cell crystals. The project involves measurements, data reduction and structure refinement of large serial femtosecond X-ray (SFX) crystallography