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programme at the Faculty of Science . The ideal candidate has a background in or experience with one or more of the following topics: SIMD performance engineering. Machine Learning. Communication-efficient
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DTU Tenure Track Assistant Professor in Nutrient-Focused Processing in Ultra-Processed Food Syste...
, 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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applicant: has a PhD degree in electrical, computer or biomedical engineering, computer science, data mining/machine learning, or a closely related area. has demonstrated the ability to perform independent
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, or other Maxwell solvers. Experience with machine learning algorithms is an advantage but not required. General qualifications Scientific production and research potential at the international level
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Associate Professor or DTU Tenure Track Assistant Professor (junior group leader) in High-through...
) to in-field testing of up to 800 strains. The scale and standardized approach will create a unique foundation for advanced data analysis, including AI, machine learning, and statistical modeling, aimed
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Associate Professor or DTU Tenure Track Assistant Professor (junior group leader) in Fermentation...
) to in-field testing of up to 800 strains. The scale and standardized approach will create a unique foundation for advanced data analysis, including AI, machine learning, and statistical modeling, aimed
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Associate Professor (Independent Group Leader) in Data Science and Modelling of Whole-Cell Biosol...
) to in-field testing of up to 800 strains. The scale and standardized approach will create a unique foundation for advanced data analysis, including AI, machine learning, and statistical modeling, aimed
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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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Source (ESS), Sweden, the European Molecular Biology Laboratory (EMBL), Institut Laue-Langevin (ILL), France, the International Institute of Molecular Mechanisms and Machines, (IMOL), Poland, and the
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contributing to developing and implementing novel algorithms at the intersection of computational physics and machine learning for the data-driven discovery of physical models. You will be working primarily with