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for innovative microfluidic platform for exosome enrichment and MS analysis The Metabolomics and Analytics Center (MAC) is seeking a talented and motivated Postdoctoral Researcher to advance the integration
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-term outcomes, EVAR-patients have an increased long-term risk of complications and reinterventions. This requires life-long follow-up. In the ZonMW-funded AI for EVAR project, we develop multi-modal
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life-long follow-up. In the ZonMW-funded AI for EVAR project, we develop multi-modal models for optimized selection of treatment before, and follow-up after EVAR. You will implement and advance
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-up. In the ZonMW-funded AI for EVAR project, we develop multi-modal models for optimized selection of treatment before, and follow-up after EVAR. You will implement and advance multimodal deep learning
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In this role, you will be responsible of developing cutting-edge deep learning models for real-time image and video analysis (e.g., segmentation, object tracking, reinforcement learning), with
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in every aspect of breast cancer image interpretation in screening, including AI, image analysis, image display, and workflow. Tasks will consist of setting up and aiding in the execution of a
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screening, and screening workflow. Finally, we will work closely with industrial partners that are involved in every aspect of breast cancer image interpretation in screening, including AI, image analysis
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what you will do You will carry experimental work in the lab, from bibliographical research, setup and protocol design to data analysis. We ask you to become independent by taking initiatives and
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conducting fieldwork, and in performing molecular labwork. You have a demonstrated ability to work with R for data analysis. Experience with, or a keen interest to learn, the analysis of metabarcoding data
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learning models for real-time image and video analysis (e.g., segmentation, object tracking, reinforcement learning), with applications to medical imaging and robotic systems. In this role, you will