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, including physics-based (white-box), data-driven (black-box), and/or hybrid (grey-box) methods. • Experience with environmental monitoring, sensor systems, and sophisticated data acquisition techniques
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leading scientists across Austria in an interdisciplinary environment spanning explainable AI, causality, knowledge representation, and neural networks. Research (90%) research in probabilistic machine
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and society. Our 7 centers specialise in the research and development of infrastructure solutions of the future, for e.g. digitisation, decarbonisation, smart cities, network security, intelligent
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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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economics Knowledge and/ or experience in one (or more) of the following areas (desirable) - Net-zero transformation - Energy economics - Hard-to-abate industries - Institutional economics or industrial
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and learning algorithms for structured data. Graphs and networks are ubiquitous in various domains from chem- and bioinformatics to computer vision and social network analysis. Machine learning with
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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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Research Fields Chemistry, process technology, engineering, toxicology, life cycle analysis The Marie Skłodowska Curie Doctoral Network “DyeAnotherWay” is inviting applications for a 36 month full time fixed
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, molecular biology, process engineering The Marie Skłodowska Curie Doctoral Network “DyeAnotherWay” is inviting applications for a 36 month full time fixed term position as a Doctoral Candidate (DC). This
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on the analysis of neuronal networks in the Drosophila brain, and the Hummel team currently consists of postdocs, pre-docs, master students and administrative colleagues who share a common interest in the function