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Tenure-track Assistant and Associate Professorship positions in Data Science and Machine Learning...
), statistics (extreme value theory, time series, functional data analysis, multivariate analysis), and bioinformatics (biological networks, multi-omics data). We are interested in both, fundamental research and
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), statistics (extreme value theory, time series, functional data analysis, multivariate analysis), and bioinformatics (biological networks, multi-omics data). We are interested in both, fundamental research and
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on Discourse Representation Theory or other semantic formalisms The positions are embedded in an active and rapidly growing research environment, including ongoing projects on, e.g., AI security, linguistically
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for monitoring, evaluating, and improving LLM robustness, e.g. building on Discourse Representation Theory or other semantic formalisms The positions are embedded in an active and rapidly growing research
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are essential, particularly in one or more of the following areas: Probabilistic or Bayesian Machine Learning Variational Inference, Ensemble, or Diffusion Models Spatio-Temporal or Sequential Modelling Graph
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following areas: Probabilistic or Bayesian Machine Learning Variational Inference, Ensemble, or Diffusion Models Spatio-Temporal or Sequential Modelling Graph Neural Networks Deep Learning and Uncertainty
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• Relational (deep) learning • Graph neural networks • Reinforcement learning These domains are central to our mission of advancing intelligent systems through principled, data-driven approaches
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because explainability is vital in health and medicine. Moreover, it leverages preferring simpler theories over complex ones if both give comparable levels of accuracy. Furthermore, it leverages the power