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is experimental and will be conducted in our lab facilities, also incorporating theoretical models of complex flow. Fieldwork is planned in collaboration with a non-profit organization in Morocco
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. Integreat develops theories, methods, models, and algorithms that integrate general and domain-specific knowledge with data, laying the foundations of next generation machine learning. We do this by combining
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technology. The planned work is experimental and will be conducted in our lab facilities, also incorporating theoretical models of complex flow. Fieldwork is planned in collaboration with a non-profit
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microscopy. Experience with cancer organoid models and/or bioinformatics is an advantage. We offer broad training possibilities in the required experimental methods within a stimulating academic environment in
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(IRT) models in small samples. The ideal candidate has prior knowledge of IRT models, a basic understanding of common estimation methods, and strong programming skills in R, Python, or another relevant
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between ice and mantle dynamics. In DYNAMICE, we will implement a framework to infer anisotropic viscosity from both ice and mantle textures in a numerical flow model. This will open new avenues
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standards within both research and teaching. The new bachelor program in bioscience is the first of its kind to include programming and computational modelling as core elements. Apply for this job Deadline
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-compliance in ecological momentary assessment, or exploring the use of machine learning techniques to aid the estimation of item response theory (IRT) models in small samples. The ideal candidate has prior
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and the ability to handle hectic periods Ability to work on problem solving, programming, data modeling and analysis, scientific writing, and public presentation Ability to work with specific
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technological progress in our increasingly digital, data-driven world. Researchers in Integreat develop theories, methods, models, and algorithms that integrate general and domain-specific knowledge with data. By