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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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science or another field related to the topic. You have experience in systematic data collection, statistical analysis with appropriate software, and, in particular, describing complex systems by simple
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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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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