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second PhD student focused on the development of bespoke probabilistic models. Thus, an affinity towards statistical modeling is important. In-depth skills in probabilistic modeling and hands-on experience
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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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that are technically well-grounded and at the same time represent stakeholder preferences. The integrated Research Training Group (RTG) will provide doctoral researchers with an attractive qualification program, foster
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The Leibniz Institute for Prevention Research and Epidemiology – BIPS in Bremen, Germany, invites applications for a three-year PhD program in epidemiology, statistics, and prevention and
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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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breakage models, e.g. with stochastic tessellations Development and implementation of estimation methods for the model parameters, e.g. with machine learning or statistical methods Lab work and collection
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system analysis or comparable Initial experience in optimization or statistics is an advantage Initial experience of an object-oriented programming language (e.g. Python, Matlab) and MS Office Analytical
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. The position is part-time, with 65% of the regular weekly working hours (currently 25.35 hours) and should be used for a doctorate. Participation in the accompanying doctoral program is compulsory. This serves
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analysis of large data sets, statistical modeling, and knowledge of at least one programming language (e. g.: R, Python and/or Julia) are required. Experience in machine learning and image recognition
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part-time, with 65% of the regular weekly working hours (currently 25.35 hours) and should be used for a doctorate. Participation in the accompanying doctoral programme is compulsory. This serves