![]() ![]() ![]() Salary and benefits (such as a pension scheme, paid pregnancy and maternity leave, partially paid parental leave) in accordance with the Collective Labour Agreement for Dutch Universities, scale P (min.You will spend 10% of your employment on teaching tasks. Full-time employment for four years, with an intermediate evaluation (go/no-go) after nine months.You will work on a beautiful, green campus within walking distance of the central train station. At least one code repository available online.Ī meaningful job in a dynamic and ambitious university, in an interdisciplinary setting and within an international network.You have a good command of the English language (knowledge of Dutch is not required).You are creative, ambitious, as well as self-motivated, proactive, and goal-oriented.You have a solid background in deep learning and deep generative modeling.You have a strong background in programming (Python) and deep learning libraries (PyTorch).You have a strong background in mathematics (linear algebra, calculus, statistics, probability theory).You have a bachelor degree and a master degree in Computer Science, AI, Mathematics, Physics, or another technical field (e.g., electrical engineering).Conduct research in Generative AI and publish papers at top conferences and in top journals.If applicable, apply your research outcomes to real-world problems.Push the state-of-the-art of Generative AI.Identify research challenges in Generative AI.Applications in Science and Technology.Joint deep generative modeling (the leading research question: How to learn a joint model, i.e., a predictive model and a marginal model with a shared parameterization?).Developing new classes of deep generative models (an example of a research question: What are new modeling paradigms for deep generative models?).Theoretical understanding of current state-of-the-art models (an example of a research question: Why do diffusion-based models perform better than other generative models? How to further improve diffusion-based models?).New learning algorithms of deep generative models (an example of a research question: How can we utilize Reinforcement Learning in the context of deep generative modeling?).Continual learning of deep generative models (the leading research question: How can we learn deep generative model in a continuous manner?).Tiny deep generative modeling (the leading research question: How can we fit current state-of-the-art models on a mobile phone?).The position is flexible in terms of topic and could be positioned within one of the following areas (but not limited to): You will participate in cutting-edge research, publish your work in leading conferences and journals for AI (NeurIPS, ICML, ICLR, AISTATS, UAI, AAAI), contribute in open-source tools, and potentially collaborate with the industrial partner to apply these tools in the real world. You will join a newly-established team under the supervision of Jakub Tomczak, and work on an exciting project in the area of Generative AI. The position will be with the Generative AI group of the Eindhoven University of Technology, which is part of the cluster Data and Artificial Intelligence.
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