33 parallel-computing-numerical-methods-"DTU" Postdoctoral positions at Aalborg University in Denmark
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characterization in complex in-situ environments. The key responsibility of the position is to develop post-processing methods to extra essential features from the collected measurement data despite drone positional
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scale. Furthermore, the work will include biomass extraction and fractionation using novel green extraction methods as well as detailed biomass chemical characterization using spectrophotometric bioassays
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. The Postdoc will conduct research on methods to enhance the performance, safety, and lifetime of lithium-ion batteries by integrating physics-based modeling with data-driven approaches. The work will include
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postdoctoral researchers willberecruited to workcloselyacross the two AAU departments of Sustainability and planning (PLAN) and Computer Sciences (CS). The project’smethodological PI is Associate Professor
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investigating the structural evolution of MOFs upon heating using techniques such as variable-temperature PXRD, DSC/TGA, and spectroscopic methods. Exploring the thermodynamic and kinetic mechanisms underlying
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Postdoctoral Position in Probabilistic Machine Learning for Spatio-Temporal Data Modelling A postdoctoral position is available at the Department of Computer Science, Aalborg University Copenhagen
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of life and satisfaction of its residents. https://www.enjoynordjylland.com/ Your work tasks The position is offered in relation to the EU-funded research program "STRONG UR, Strategies for optimized
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The project may address national or international problems, and should do so using appropriate methods, qualitative and/or quantitative. Access to Danish data sources, such as registry data, respondents
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characterization with scanning electron microscopy is a plus Experience with computational tools such as MATLAB, Python or relevant tools Ability to work independently and collaboratively in a multidisciplinary team
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. Your competencies We thus imagine that you: have a strong background in digital signal processing and machine learning; have substantial experience with scientific computing in Python/C++/ROS; know