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Field
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Patient-derived organoids are the hallmark of personalized medicine with seemingly endless possibilities to match the right treatment to the right patient. As organoid data are often longitudinal in
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on developing advanced machine learning models to quantify phenotypic traits of crops, including corn, soybean, and other selected species. These models will leverage data collected from various sources, such as
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contribute to the design and development of Machine Vision approaches for the quantitative analysis and phenotyping of agricultural systems: Training/Development of computational models for the quantitative
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Research Infrastructure? No Offer Description We are looking for a researcher to work on the finite element modelling of the interaction between textile materials (yarns and fabrics) and textile
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the most efficient analytical approach (e.g. weight, profilometry, SEM) to calibrating the quality model? How can AI based methods be used to fit empirical data to existing nanofiber quality models
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Your job Are you fascinated by using mathematics to solve fundamental questions in ecology? Do you thrive on translating abstract models into biological insight? If so, this PhD opportunity could be
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on atomic scale, requiring the development and study of ever more realistic model systems. Single atom catalysts, where the catalytic site contains only a single metal atom supported on a heterogenous
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for pavement lifetime prediction, primarily in Dutch conditions. Foreseen challenges include data harmonization, key relationship extraction, scalability, metadata structuring, predictive modeling, and data
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Infrastructure? No Offer Description Are you fascinated by using mathematics to solve fundamental questions in ecology? Do you thrive on translating abstract models into biological insight? If so, this PhD
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biology and bioinformatics, as well as in Machine Learning (including Large Language Models). Good understanding of evolutionary and molecular biology concepts, and good statistical (data analysis) and