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, utilisation of natural resources, shipping, predictive modelling, or climate risk Core courses in probability and statistical inference, optimisation, microeconomics, scientific methods Elective courses in
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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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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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work with fish behavior, engineering geology, turbine design, variable speed operation, etc. It involves fundamental research including a literature study and CFD modelling with the use of real case
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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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/or application areas such as the ones listed below: CROSS-DISCIPLINARY RESEARCH Nanomaterials &Nanofabrication Nanocharacterisation Modelling and simulation APPLICATION AREAS OF RESEARCH Health Energy
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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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, especially in ultracold quantum gases or condensed matter theory Proven analytical, computational, and modelling skills Experience with numerical simulations of quantum or many-body systems A deep curiosity
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The doctoral student project and the duties of the doctoral student This Data Driven Life Sciences (DDLS) PhD project focuses on probabilistic models of protein structure, which can be used primarily