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rapidly evolving retrieval paradigm where generative models are used to directly generate document identifiers given a user query. This paradigm departs from traditional multi-stage retrieval pipelines and
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applications involving image analysis, real-time monitoring, or complex process optimization. You have hands-on experience with model optimization techniques such as post-training quantization (PTQ
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well as working with organ-on-chips and imaging of these devices will be considered as a benefit; Excellent analytical skills and an innate ability for solution oriented problem solving; Team player with great
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holders, setting requirements on data quality and measurement conditions. Together with cardiologists, supervisors and colleague PhD students, you will further perform human testing of several prototype
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-oriented mindset, and a passion for (scientific) challenges, you are the right person for us. Our lab develops technologies that integrate advanced imaging, computational analysis, and single-cell & spatial
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(GenIR), a new and rapidly evolving retrieval paradigm where generative models are used to directly generate document identifiers given a user query. This paradigm departs from traditional multi-stage
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will image them using a variety of microscopy methods, and collaborate with a team of computer vision scientists to build ML-based models for phenotype prediction, helping to accelerate the cell
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, productivity, and overall operational stability of the process plants can be determined. This rigorous analysis will provide a clear picture of the flexibility potential and set the stage for implementing
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Technology are also welcome, particularly if their thesis work involved medical robotics, control systems, or image-guided interventions. Experimental Skills: Experience with experimental research in robotics
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rehabilitation center, and will be embedded in the Vision and Imaging Data Analytics group at the Department of Intelligent Systems and Centre for Cognitive Science and Artificial Intelligence at Tilburg