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Job Description The Quantum Physics & Information Technology (QPIT) group at DTU Physics is seeking exceptional individuals to join our team as PhD students. We specialize in quantum information
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based on transcriptomic data of faba beans. This includes: Implementing the bioinformatics tool Conserved Unique Peptide Patterns (CUPP) to predict CAZyme activities during faba bean cell wall synthesis
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machine learning to analyse decision-making using diverse data sources, including physiological process data from immersive virtual reality experiments? Do you want to apply cutting-edge modelling and data
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of the general degree programmes at DTU. For information about our enrolment requirements and the general planning of the PhD study programme, please see DTU's rules for the PhD education . We offer DTU is a
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. For information about our enrolment requirements and the general planning of the PhD study programme, please see DTU's rules for the PhD education . Assessment Professor Søren Kegnæs and Accociate Professor Jerrik
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on the most advanced theories, models, using first-hand cases and data from the wind energy industry, to lift our understanding of wind and wave characteristics during storms in the presence of wind farms
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company, where you’ll take wind farm design and simulation tools to the next level. By fusing cutting-edge physics-based modeling with rapid, data-driven engineering, you’ll develop innovative solutions
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. Using a novel fluorescence microscopy method, you will track bacterial responses to secondary metabolites produced by neighboring bacteria. You will link these observations to microbial gene expression
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. Experience with simulation tools, including Isaac Gym, Isaac Sim, Aerial Gym. Experience with ROS, and especially real-life aerial robots. Experience with open-source tools for deep learning, computer vision
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desirable, but not essential skills for both projects: Proficiency in molecular biology techniques, such as (q)PCR Experience in computational data analysis, e.g., for scRNA-seq You must have a two-year