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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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cells. Typically, the specificity, speed, and directionality of transport are tightly woven into the ordered structure of the pore which is characterized by a limited conformational flexibility
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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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, 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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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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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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advancing image-guided precision irradiation and realistic disease modelling. As postdoctoral researcher, you will contribute to cutting-edge developments in preclinical CT imaging, precision irradiation, and
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Research Institute for Oncology and Reproduction, the MAASTRO Physics Research Division plays a leading role in advancing image-guided precision irradiation and realistic disease modelling. As postdoctoral
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, and directionality of transport are tightly woven into the ordered structure of the pore which is characterized by a limited conformational flexibility. Remarkably, nature also offers a fascinating and
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of Science at UvA. What are you going to do? The aim of the project is to use advanced Machine Learning techniques to predict the anharmonic vibrational spectra of large Polycyclic Aromatic Hydrocarbon (PAH