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supervised models on downstream regression tasks. A key challenge lies in effectively modeling the temporal nature of EO data. Since downstream applications require varying temporal resolutions and sequence
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different types of experimental data to establish reliable methods for identifying physically meaningful model parameters and assessing model accuracy under dynamic operating conditions. In a later stage
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of atomic-resolution structural and spectroscopic data. Your Profile Completed qualification to enroll for the Master thesis in Physics or Materials Sciences, with a good track record Willingness to
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<span lang="en">Leipzig University</span> | Leipzig, Sachsen | Germany | about 21 hours ago
experiment with theory
- Hands-on experience in optics, video microscopy, particle tracking and/or microfluidics
- Programming experience for data analysis and experiment automation (Python
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well as to allow video information to be shared for both marketing, analytics and editorial purposes. By accepting optional cookies, you consent to the processing of your personal data - including
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PhD Position - Operando X-ray Characterization of Catalytic Interfaces for Chemical Hydrogen Storage
XFEL facilities. Analyze experimental data and develop or adapt data-analysis workflows, including scripting in Python or comparable tools. Combine spectroscopic information with catalytic performance
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | 27 days ago
anomalous state. We are seeking a postdoctoral scholar to conduct in-depth analysis of stratospheric data, using data from the Microwave Limb Sounder (MLS) as well as complementary datasets like the
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Umeå Proteomics Platform. https://www.umu.se/en/research/infrastructure/umea-proteomics-platform/ The project is led by Sandra Jämtgård, Department of Forest Ecology and Management, SLU in
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Helmholtz Association of German Research Centres | Bremerhaven, Bremen | Germany | about 2 months ago
well as to allow video information to be shared for both marketing, analytics and editorial purposes. By accepting optional cookies, you consent to the processing of your personal data - including
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STFP Home sign in | focus RAP opportunity at National Institute of Standards and Technology NIST Leveraging Artificial Neural Networks for Enhancing GC and LC-MS Metabolomics Data