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Assistant Professorship (all genders) - Tenure Track Graph Machine Learning
• Wien
Assistant Professorship (all genders) - Tenure Track Graph Machine Learning TU Wien (Vienna) is Austrias largest research and educational institution in the field of technology and natural sciences. The TU Wien Faculty of Informatics seeks to fill the open tenure-track position of an Assistant Professor (all genders) of Graph Machine Learning for 20 hours/ week. The position is affiliated with both the Databases and Artificial Intelligence Unit, part of the Faculty of Informatics, and the ÖAW-AITHYRA-Research Institute for Biomedical Artificial Intelligence. The estimated starting date is June 2025. The work contract is initially limited to six years. The candidate and TU Wien can agree upon a tenure evaluation, which when positive, opens the possibility to change the position to Associate Professor [...] graph neural networks, graph transformers) Design of novel methods for a wide array of tasks in graph machine learning, including node-level, link-level, and graph-level tasks Design of novel methods for critical life-science domains, including the biochemical domain (e. g. ,
drug discovery) Graph foundation models: Development of foundation models for graphs by building on the success of large language models Theory of graph machine learning and geometric deep learning: symmetry, inductive bias, expressive power, generalization, extrapolation, convergence Logical foundations of graph machine learning: logic of graphs, descriptive complexity of graph neural networks, uniform expressiveness Interpretability and explainability of graph learning through logical methods Design of graph machine learning solutions for different types of graphs, ranging from simple graphs to knowledge graphs Adaptation of graph machine learning techniques to relational databases and associated tasks A successful candidate should have a relevant postdoctoral experience and a compelling research vision. We expect publications in top-tier ML (NeurIPS, ICML, ICLR) and AI conferences (IJCAI, AAAI) [...]
