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project focused on developing an advanced machine learning framework for spatio-temporal datasets. The position is for 2.5 years and is partially funded by the Dutch Research Council (NWO) through
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, including bioacoustics algorithms developed in the team. What you will do Conducting rigorous research at the intersection of ML and wildlife bioacoustics; Actively participating in regular group and one
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elegant APIs and intuitive, welcoming, user-centered interfaces; Definition and development of agentic (user)interfaces to OpenML; Contribute to OpenMLs’ federated position ensuring that the platform
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the project. What you will do Conduct original and high-quality research in machine learning and computer vision; Develop novel algorithms for adapting and specialising visual foundation models; Publish
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; Develop novel algorithms for adapting and specialising visual foundation models; Publish research findings at leading machine learning and computer vision venues such as CVPR, ICCV, ECCV, NeurIPS, and ICLR