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raises deep and largely unsolved challenges. As a postdoctoral researcher, you will tackle exactly this question: how to generate code with AI and formally verify that it does what it should. Your work
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modern deep learning frameworks (PyTorch, JAX, or equivalent). Have good software engineering habits — modular, well-documented, reproducible code. Are comfortable working in interdisciplinary teams and
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description Work on EU projects to develop next‑generation transport, emission and health forecasting models by integrating deep learning, xAI, and diverse data sources such as traffic sensors, smart‑card data
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years prior to the application deadline. Experience with machine learning for scientific applications. Experience with deep learning frameworks such as PyTorch or TensorFlow. Experience with atomistic
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leverage reinforcement learning, deep learning, and generative AI, and evaluate against the research front in mathematical optimization strategies, to enable efficient, robust, and adaptive evacuation
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infrastructure, mobility demand, and power grid operations. On top of this environment, a deep-learning-based learning will be developed to enable decentralized and coordinated decisions on EV user charging