2,408 model-driven-development "Integreat Norwegian Centre for Knowledge driven Machine Learning" PhD positions
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distances from the spatial structure of genetic genealogies across the genome, and the genetic relatedness among individuals; or develop and use biophysical models (hydrodynamics + particle tracking
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research in data-driven nutrition, health, and food science. With large-scale diet and health data, omics data, biomarkers, digital food and health services, we establish predictive models for evaluation
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to develop engineering interventions to improve plant regeneration, seed longevity and defenses against disease. Your task will be to further develop two-dimensional and three-dimensional models of plant
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Develop advanced models to understand and predict piping and internal erosion in dikes. As a PhD researcher at TU Delft, you will connect fundamental fluid–soil interaction physics with
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, prestress transfer, and reactivation. Structural-scale simulation of SURPASS overlays in strengthened members, including parametric finite element analyses for surrogate-model development and digital-twin
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the development of artificial-intelligence models. Its subtle infiltrative growth pattern also creates specific challenges for diagnosis, staging and clinical management. This PhD project is part of M4GIC-ILC, a 36
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realistic oxide nanoparticles with sizes from a few 10s of atoms to several 1000s of atoms. In each case, machine learned interatomic potentials (MLIPs) will be developed to describe their structure and
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sufficiently robust, the experimental system may be progressively developed to explore more complex geometries, time-varying volume changes and increasingly physiologically representative cardiovascular models
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element analyses for surrogate-model development and digital-twin support. Large-scale experimental assessment of volumetrically prestressed SURPASS overlays for non-planar structures, including
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generate biologically interpretable models of zoonotic emergence and ultimately aid in developing new tools for human pathogen surveillance. This project offers training in bioinformatics, data science and