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Field
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are looking for a motivated and capable researcher who is eager to grow into this opportunity. The selection panel will use the following criteria: Familiarity with crop simulation models (e.g. APSIM, DSSAT
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. Although there is a clear synergy between fatigue damage and corrosion, most fatigue prognosis models do not explicitly consider the role of the environment, which is usually reduced to obscured fitting
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. The focus is on automatic emotion detection in text, with special attention to crosslingual differences in emotion verbalization and to how multilingual models deal with such differences. You will publish
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to the PhD project ie. processing and analysis of dietary intake data, statistical analyses (eg. linear mixed models) as well as evaluation of child growth and body composition data. Relevant publications
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found in the areas of: Human-Technology Interaction Form and Function Modeling and Simulation Product Development Material Production and in the interaction between these areas. The research covers
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Additional preferred expertise and experience Experience with longitudinal data analysis and advanced statistical methods (e.g. linear and generalized mixed-effects models, growth curve analysis and structural
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approaches in root phenotyping, image analysis, or simulation modeling to understand the functional roles of plant roots in agroecosystems. You have excellent communication skills and will to collaborate with
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of topics include algorithmic fairness in network analysis, developing network embedding frameworks for real-world network datasets or AI models based on agentic LLMs for simulating real-world network data
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in healthcare service and opportunities for identification of such deviations using computer vision approaches. It will demonstrate how deviation data can be used in computer-based simulation models
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/or application areas such as the ones listed below: CROSS-DISCIPLINARY RESEARCH Nanomaterials &Nanofabrication Nanocharacterisation Modelling and simulation APPLICATION AREAS OF RESEARCH Health Energy