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-based metadata platform that you will help develop. In collaboration with stakeholders from energy research, you will develop methods to increase data and software interoperability, enabling the automated
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Framework Programme? Horizon Europe - MSCA Reference Number DC3 Marie Curie Grant Agreement Number 101225914 Is the Job related to staff position within a Research Infrastructure? No Offer Description Ageing
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the testing of newly devel-oped materials and the use of machine learning methods to process complex data sets. The focus is on techniques such as ultrasound, radar, computed tomography, acoustic emission
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-oriented way of working Fluent English (spoken and written) Publications at top-tier computer vision conferences or journals is a plus Experience with open-source software development is a plus We offer A
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, you will develop highly accurate computational tools for predicting satellite features in XPS spectra of 2D framework materials. Your work will be based on the GW approximation within Green’s function
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computational tools for predicting satellite features in XPS spectra of 2D framework materials. Your work will be based on the GW approximation within Green’s function theory. While the GW method reliably
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Computer-adaptive methods and multi-stage testing Application of machine learning in psychometrics Predictive modeling of educational data Methodological challenges in cohort comparisons Advanced meta
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jointly run by the Max Planck Institute for Informatics (MPI-INF), the Max Planck Institute for Software Systems (MPI-SWS), the Computer Science Department at Saarland University, and the
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, their achievements and productivity to the success of the whole institution. At the Faculty of Mathematics, Institute of Scientific Computing, within the Dresden Center for Computational Materials Science (DCMS
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experience and enthusiasm for experimental work Basic knowledge of instrumental and preparative chromatography Fluent in written and spoken English Confident handling of common analytical software (e.g. Excel