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as of that date be with a department Contact information For further information, please contact: Prof. Alfred Spormann, aspormann@inano.au.dk. Application procedure Short-listing is used. This means
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Faculty position in Molecular Health (Tenure-Track Assistant Professor / Associate Professor) at ...
employment is Aarhus University with related departments. Contact information For further information, please contact: Head of Department, Claus Oxvig. Phone number: +45 30362460 Email: co@mbg.au.dk Deadline
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properties through computer simulations. The project also includes validation of materials in the lab and translating the findings into practical recommendations for use in real power-electronics environments
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sets, lexicon development, use of instrumental techniques to correlate or predict sensory characteristics and multivariate data analysis. This position is part of an interdisciplinary research project
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to the faculty’s departments. Consequently, your employment will as of that date be with a department. Contact information For further information, please contact: Professor Troels Skrydstrup, +45 28 99 21 32, ts
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Electrophysiological characterization of muscle fiber excitability (in collaboration with the research group) In vivo studies using animal models of neuromuscular disease Integration of molecular and transcriptomic data
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Job Description Are you passionate about environmental contaminants, food safety, marine ecosystems, and creating real-world impact through cutting-edge analytical and data-driven approaches? Do you
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Postdoc position to support international research and capacity-building projects employing elect...
of large-scale EM data for groundwater mapping. Teaching and training of Ethiopian partners and students in EM methods, data processing workflows, inversion software, and geological interpretation
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geological interpretation of large-scale EM data for groundwater mapping. Teaching and training Ethiopian partners and students in EM methods, data processing workflows, inversion software, and geological
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assessment. Design and train reinforcement learning agents to optimize operational safety. Build and validate dynamic Bayesian network models integrating empirical and synthetic data. Conduct scenario-based