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application-oriented research that unlocks the potential of data through rigorous analysis – advancing solutions in societally relevant domains. Your profile Master’s degree in Statistics, Industrial
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reuse of energy systems analysis processes. In line with FAIR and Linked Open Data principles, you will design interfaces that enable the smooth processing of big data in the context of scientific, AI
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collaborate closely with a postdoctoral researcher responsible for in-situ fatigue testing under corrosive environments, and will participate in the 4D (x,y,z,time) analysis of the AM microstructure and crack
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-field methods) Multiscale mechanics and microstructure-property relationships Python/C++/Matlab-based simulation and data analysis Industry-facing research and technology transfer You will also benefit
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, energy-related datasets. Proficiency in Python, MATLAB, and/or Julia for modeling, simulation, and data analysis. Familiarity with GIS tools (e.g. QGIS), time-series databases (e.g. InfluxDB), and version
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analyses by age, ethnicity, and index of multiple deprivation will be performed. The second stage of the study will involve the analysis of prospectively collected EQ-5D-5L data from a cohort of patients to
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, hierarchical and composable analysis and design is needed. The project will leverage tools from contract-based design theory to formalise such security and performance guarantees at multiple resolutions
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analysis, next-generation sequencing, and small animal models. Salary and social benefits will be determined by the regulations of the German TV-AVH (salary agreement for public service employees
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their impact on bladder function under physiological and pathological conditions. Work will include data acquisition, analysis, and interpretation, as well as collaboration with clinicians for human
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animal behaviour, statistics, and computer-based data analysis. documented research experience with farm animals is an advantage. strong communication skills in English (spoken and written). As a person