142 evolution-"https:"-"https:"-"https:"-"https:"-"https:"-"The-University-of-Edinburgh" positions in Austria
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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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addition to providing a solid academic education, we also place a special emphasis on the personal development of students. We support students in developing curiosity and critical thinking, thereby creating a solid
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“Exposome Austria Non-targeted Lab”. This position in the field of bioanalytical chemistry is dedicated to the development of innovative mass spectrometry-based workflows and data evaluation tools
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Cluster of Excellence quantA. The group’s research combines the development of scalable photonic quantum technology for quantum computing and other quantum information applications with the investigation
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digitalization. To achieve our goals, we rely on our specific research, development and technology competencies, which are the basis of our commitment to excellence in all areas. With our open culture
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scraping multiple data sources, most notably on the video game development industry and various sports (e.g., ice hockey, basketball, and soccer), or by collaborating with organizations. Recently, he has
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| Environment | Development, which aims to conduct theoretically grounded and empirically informed research at the intersection of population dynamics, environmental change, and resilient development. We
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expertise in high-performance computing, artificial intelligence, and data ecosystems, creating an interdisciplinary innovation environment for research, development, start-ups, and industrial projects. AI:AT
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software development for astronomy-related projects, preferably in data flow systems or data reduction pipelines. Experience with the ESO DFS software stack, such as EDPS, EsoRex, CPL, etc. A PhD / Doctoral
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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