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analysis of large-scale timeseries data, applied to advance the fundamental understanding of battery aging and enable new diagnostic capabilities for real-time battery monitoring. Duties A postdoctoral
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candidate must have excellent written and oral English skills and experience in synthesis and analysis of high-entropy alloys. Desirable qualifications Experience in X-ray diffraction methods, battery
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participatory environment are key elements in our growth. The 60 doctoral students within the department are a diverse group from different nationalities, backgrounds and fields. We offer very good employment
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: Conducting experimental studies on radionuclide sorption onto cement phases Performing spectroscopic studies with XPS to determine metal oxidation states Participating in DFT calculations on metal sorption
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. In this project, you will have the opportunity to combine molecular biological methods with field studies and data analysis to enhance preparedness against forest diseases and promote sustainable
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of the following areas: state models, time series analysis, computational statistics, unsupervised machine learning, optimisation, model predictive control. Experience in financial mathematics. Having high integrity
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principles, and computer-based analysis methods. The research will include investigating aggregated data from genetics, archaeology and linguistics Requirements PhD degree in Population genetics
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analysis, statistical modelling, linear mixed models, and machine learning among others. The position is well suited for an individual interested in quantitative genetics and data analysis that wishes
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lymphoblastic leukemia (ALL). This will include RNA-sequencing of single leukemia cells, bioinformatic analysis of the data, follow-up analyses, and functional experiments. You will be responsible for executing
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analysis of complex, longitudinal, and high-dimensional data (e.g., immunometabolic profiles, clinical data, biomarkers). Development and application of predictive models and algorithms for diagnostics