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(subproject A1): This project aims to enhance smartphone-based survey methods as one component of future multi-method travel surveys, to achieve representative samples and travel estimates, to collect
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or replace established methods from computational engineering and computer simulation (such as the finite element method) to represent and exploit relationships along the composition-process-structure-property
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Brandenburg University of Technology Cottbus-Senftenberg • | Cottbus, Brandenburg | Germany | about 8 hours ago
them to work on innovative research topics and to develop and apply the scientific methods appropriate to their research topics. Course organisation During the three-year programme, doctoral students
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excursions. The PhD student will work on analysing the reliability of paleomagnetic records, deriving uncertainty estimates, and building time-dependent models of the paleomagnetic field evolution using a
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. Applicants should have experience with tissue culture and standard molecular biology methods. Basic knowledge of computer programming (using the R software environment) and hands-on experience working with
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Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung | Bremen, Bremen | Germany | about 1 month ago
the new suite of powerful data science methods will enable novel insights into the structure and functioning of deep-sea ecosystems, while the developed approaches will be available for the analyses
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The Leibniz-Institut für Analytische Wissenschaften - ISAS - e. V. develops efficient analytical methods for health research. Thus, it contributes to the improvement of the prevention, early
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hydrological modelling methods that explicitly use interpolation to pre-process precipitation data. In addition, the research should explore the integration of opportunistic sensor data to improve forecast
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processing and machine learning methods, and big data analytics solutions to extract highly accurate large-scale geo-information from big Earth observation data. Our team aims at tackling societal grand
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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