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, bioactive compounds, and other key nutrients. Develop and apply machine learning and modeling techniques to analyse, predict, and optimize the effects of processing on food composition, food Ingredient
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for Industrial Mechanics is located at SDU's beautiful campus in Sønderborg, in the inspiring building of Alsion, which is a center for science, culture and learning in the heart of Sønderborg and perched
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of precision medicine by developing innovative statistical genetics methods, implementing state-of-the-art machine learning algorithms, and integrating artificial intelligence to uncover novel biological
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. These include, but not limited to: Research Question 1: How can multimodal UAV data (RGB, thermal, LiDAR, hyperspectral) be fused using machine learning to predict complex canopy traits such as water-use
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decision support tools by integrating health data, domain knowledge, and machine learning. Key objectives include improving diagnosis, monitoring, and treatment through early detection of deterioration
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tools (e.g., statistics, machine learning, optimisation, simulation) to healthcare delivery, healthcare operations and healthcare management as well as medical decision support. Your role is to build
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focused on applying quantitative tools (e.g., statistics, machine learning, optimization, simulation) to healthcare delivery, healthcare operations and healthcare management as well as medical decision
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often related to domesticated species and humans, but increasingly also on other organisms. Our focus areas include quantitative genetics, deep learning, machine learning, population genetics, integrative
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on quantitative methods such as applied simulation, big data, artificial intelligence, and machine learning as well as an ability to apply such skills to interventions research, field experiments, and
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specialized areas: Machine Learning / Deep Learning Uncertainty Quantification Wind Farm Flow Modelling Wind Farm Control Wind Farm Design Wind Farm Control Co-design Hybrid Power Plant Design & Control Co