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Intelligence, Applied Mathematics, Electrical Engineering, or a closely related field. You have demonstrated expertise in machine learning and deep learning, with experience in time series forecasting or related
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You hold a PhD in Computer Science, Artificial Intelligence, Applied Mathematics, Electrical Engineering, or a closely related field. You have demonstrated expertise in machine learning and deep
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track record in one or more of the following fields: (1) human-computer interaction, collaborative AI, (2) Generative AI/machine learning, (3) interaction design, experimental design, or evaluation
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for the efficient training and fine-tuning of machine learning models. The postdoc will closely collaborate with researchers at the Dutch Language Institute (and Radboud University Nijmegen). Selection Criteria PhD
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extensive knowledge on zooplankton imaging techniques ability to program and train machine learning models for automated image classification experience with shipborne campaigns and ready to join multi-week
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together many prominent AI researchers in the Netherlands. The vision of the project is to design Hybrid Intelligent systems, an approach to Artificial Intelligence that puts humans at the center, changing
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skilled in object-oriented coding (preferably Python) and data analysis; affinity with machine learning and explainable AI techniques, preferably in a geoscience context; good social skills. As a university
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, the identification of predictive features, and the construction and validation of statistical or machine-learning-based models. The postdoctoral researcher will be responsible for: Developing a
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(HIMS), in close collaboration with industrial partner BOR-LYTE and Smart Industry testbeds. This position offers a unique opportunity to combine inorganic chemistry, spectroscopy, machine learning, and
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and Liu, Supervised learning in physical networks: From machine learning to learning machines, PRX 11, 021045 (2021) [2] Stern and Murugan, Learning without neurons in physical systems, Ann Rev Cond