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, heavily relying on clinician expertise. This project funded by the Hanarth fund combines ultrasound imaging with histopathology data to train advanced AI models for automatic tumor segmentation, enabling
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deep learning algorithms. We welcome applications from individuals with experience in: Experience developing deep learning models for real-time image/video segmentation, object tracking, reinforcement
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within a cross-functional team, including software developers, electrical and mechanical engineers. Experience and strong understanding of machine learning algorithms, mathematical modelling, and
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interpretation is subjective, heavily relying on clinician expertise. This project funded by the Hanarth fund combines ultrasound imaging with histopathology data to train advanced AI models for automatic tumor
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and Mission Science team located at ESTEC (Noordwijk, Netherlands) to align the development of AI-driven methodologies and algorithms with the CHIME mission. Technical competencies Knowledge relevant
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, employees, IT infrastructure, specialized training). Second, they may require the use of quantitative models, data analysis, and algorithms, but these applications must also safeguard the data privacy and non
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opportunity to tackle these two complementary perspectives. In the first direction, you will develop advanced system identification techniques that combine nonlinear dynamics theory with machine learning tools
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the first direction, you will develop advanced system identification techniques that combine nonlinear dynamics theory with machine learning tools. The goal is to extract governing equations directly from
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particle physics, perform data analysis and develop object reconstruction algorithms in the ATLAS experiment. You will become a member of the ATLAS collaboration and will be based in Nijmegen. Furthermore
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Europe, Altair, MIT and 12 other partners to build an AI Partner in Engineering (AIPE) that converses with engineers, proposes designs, explains its reasoning and even writes new optimisation algorithms