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Learning with Graphs led by Prof. Nils M. Kriege. Our research focuses on the development of new methods and learning algorithms for structured data. Graphs and networks are ubiquitous in various domains
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(4DSTEM). This approach will combine three-dimensional charge distribution data, generated through atomistic simulations, with machine-learning-driven modelling to guide and refine the phase reconstruction
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stakeholders and an analysis of TIA clinic data you will help to understand how stratification might assist in delivery of more appropriately targeted care. You will develop mixed-methods expertise and join Dr
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Master’s degree in a relevant scientific field, such as soil science, environmental science/chemistry, ecology, or agronomy. Strong academic record in statistics and data analysis. The following experiences
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university. More information about us, please visit: the Department of Biochemistry and Biophysics . Project description Project title: Perturbation-based Multi-omics Inference of Gene Regulatory Networks
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affect plant performance across environments. The project follows an integrated experi-mental approach across laboratory, greenhouse, and field scales, combined with advanced phenotyping and data-driven
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of wind turbines. Despite remarkable progress in structural health monitoring boosted by AI, purely data-driven models have no physical interpretability and poor generalization capabilities. Thus
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-time Research Assistant (RA) wanted for an exciting, large-scale project in the laboratory of Professor Randy Buckner. Job-Specific Responsibilities: The RA's primary responsibilities include: (1) data
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details of two referees The deadline for application is March 1st, 2026. For more information about PFT group, please check on our website Particle and Fiber Technology The position is suitable for disabled