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of elements) of the model.; 3) develop an optimization algorithm based on genetic algorithms and metamodels and 4) design functionally graded OC scaffolds using different biomaterials. The doctoral candidate
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); execute PoCs and tech transfer with foundries, equipment/materials/metrology vendors. Data & Platforms: Establish robust data governance and MLOps pipelines; develop reusable algorithms and prototype
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garden experiments to test how plant performance is determined by plant genotype, the environment (above- and belowground parasite and warming in different combinations and sequences), and their
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function in similar experiments with different combinations of altered temperature and added parasites. The main work of the PhD candidate entails quantitative genetics experiments testing for G×E. The
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this data. Clustering travel needs. To define different mobility needs and motivations based on the travel data, we apply different clustering algorithms (e.g., traditional k-means, density-based clustering
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normalization and integration of data from different sources, defining appropriate strategies to deal with all ethical and privacy/security requirements; Contribute to the development, validation and integration
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an innovative academic education to more than 20,000 students; conduct pioneering scientific research and play an important service-providing role in society. With more than 6000 employees from 100 different
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. An optimisation tool has been developed that uses a genetic algorithm to optimise the location of BGI taking surface water flood risk reduction and the cost of different interventions into consideration. This PhD
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networks, leading to different forms of diabetes. By combining human genetics, regulatory genomics, and genome editing, they aim to uncover disease mechanisms and design strategies to restore or regenerate
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construction and visualization of pangenomes for crops with large genomes Summary: Pangenomes are highly relevant for grains RD&E pre-breeding research because they capture the full spectrum of genetic diversity