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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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can we measure gravity of microscopic systems?”. Such questions and their implications for the foundations of physics are the driving force behind our research. You will be part of our team and develop
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as evidence of ongoing CIN. This PhD will work at the leading edge of single-cell transcriptomics and modern statistical/AI methodology to address this gap using in-house developed cell atlases. We
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measure gravity of microscopic systems?”. Such questions and their implications for the foundations of physics are the driving force behind our research. You will be part of our team and develop new ideas
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-cell transcriptomics and modern statistical/AI methodology to address this gap using in-house developed cell atlases. We will develop and benchmark approaches that infer copy-number changes and CIN
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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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. You will be part of our team and develop new ideas, technologies and experiments to provide new insights on macroscopic quantum physics, on gravity at small scales and, in the long run
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. The Wegener Center integrates climate, environmental, and socio-economic research and develops pathways toward a low-carbon, climate-resilient future. We analyze climate and social systems, offer a specialized