28 learning-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"CNRS" Postdoctoral positions in Netherlands
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and decision-making. Working with real-world data from Alliander, you will publish at leading machine learning venues while building tools with tangible impact on the Dutch energy sector. The Dutch
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criteria: A PhD (obtained, or nearly completed) in Natural Language Processing or a closely related area. Solid knowledge of machine learning, especially deep learning. Experience in model development
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foundational AI and machine learning models (e.g., multimodal AI, large language/world models) with specific finetuning for ELEVATE; designing geographically context-sensitive urban design recommendations that
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postdoctoral position focuses on text and image feature learning for news ecosystems, analysing the complex multidimensional feature space of visual information to support data-driven journalism. This
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civic participation. The research in this postdoctoral position focuses on text and image feature learning for news ecosystems, analysing the complex multidimensional feature space of visual information
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for sustainable sediment management. This will be done for two case studies, namely Western Scheldt and Wadden Sea. To facilitate knowledge exchange and the learning process, interactive workshops
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preferred candidate; there is budget for support in technology development. You will work closely with a PhD researcher at the German partner who focuses on the underlying machine learning models, and
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collaborative environment in which you have the freedom to work independently, while also contributing to a shared goal. You take a mastery-oriented approach to your own learning and development and are eager
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problem. You will develop a design-build-test-learn cycle, combining high throughput experiments and active learning to obtain synthetic cells with the desired properties. You will integrate liquid handling
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learn, and how does early learning influence later intelligence? Join our interdisciplinary research team to develop and empirically test innovative Bayesian cognitive models that reveal the hidden