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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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(postdoc) Limited until: 14.10.2032 Reference no.: 5906 Explore and teach at the University of Vienna, where over 7,500 brilliant minds have found a unique balance of freedom and support. Join us if you’re
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Stanford Departments and Centers: Environmental Social Sciences Postdoc Appointment Term: 12 months renewable for an additional 2 years based on satisfactory performance and availability of funding
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in higher adelic analysis and geometry, applications of algebraic K-theory in arithmetic geometry, in anabelian geometry and IUT, in Diophantine geometry, in applications of modern mathematics to deep
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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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future. Fueled by curiosity and a deep sense of duty, they contribute invaluable insights to research and teaching, enriching our society. Are you inspired and driven by the desire to make a meaningful
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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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) Positions Postdoc Positions Application Deadline 10 Jul 2026 - 23:59 (Europe/Paris) Country France Type of Contract Other Type of Contract Extra Information Fixed-term contract (CDD) Duration: 24 months Job
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mediation produce, or fail to produce, a deep and distanced historical understanding. The central challenge is to understand how certain configurations of the design space support an active construction