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for mental health management. The PhD student will be tasked with conducting methods research to advance the methodological approaches used in evidence synthesis in nutrition research and the development
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interest in 3D modeling, generative methods/scripting, parametric design, AI methods, visualization, digital fabrication Didactic talent and enjoying interdisciplinary working and learning methods
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Develop machine learning methods and tools with a specific focus on: Data-Centric AI: Including data attribution, data curation, and privacy preservation for large foundation models (e.g., LLMs and VLMs
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are excited to push the boundaries of responsible AI. Learn more about the lab's work at: https://martinpawelczyk.github.io/ . Tasks and Responsibilities Develop machine learning methods and tools with a
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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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Your responsibilities: As a University assistant, you will contribute to the work group Machine Learning with Graphs led by Prof. Nils M. Kriege. Our research focuses on the development of new methods
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research focuses on the development of new methods and learning algorithms for structured data. Graphs and networks are ubiquitous in various domains from chem- and bioinformatics to computer vision and
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What you’ll be doing In the Complex Dynamical Systems Group (Prof. Andreas Kugi) and in close cooperation with an internationally active, industrial research partner you will develop new methods
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, in particular in quantum phase-space methods. • You have a proven experience in numerical methods and programming, particularly the simulation of PDEs. • Excellent written and spoken English. What we
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to the development of non-destructive methods to monitor natural degradation, using advanced analytical and statistical approaches. • Develop, implement, and refine models that integrate micro-environmental