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- Erasmus MC (University Medical Center Rotterdam); Rotterdam
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quality that is not visible in blood or clinical characteristics. By combining the results of AI-driven image analysis of histological samples conducted in this PhD project with biomarker data and outcome
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team of experienced researchers in imaging, machine learning, oncology, and pathology. We do not discriminate on the basis of sex, gender, belief, culture, place of birth or occupational impairment when
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on the development, optimization, and clinical evaluation of new x-ray-based imaging methods. The lab focuses on the use of medical physics approaches to improve image acquisition methods and processing algorithms
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Welcome to Maastricht University! The Computational Brain Connectivity lab (CBClab) at Maastricht University is looking for a PhD to investigate Human Cortical Angioarchitecture with 3D Histology
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that has been generated in a prior laboratory-setting project. Specifically, we will integrate recent advances in artificial intelligence-based automated interpretation of medical images, and new knowledge
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crystallization happens in a device and how does this impact power output? How can Magnetic Resonance Imaging (MRI) and X-ray Computed Tomography (CT) be used to visualize and analyze in-situ processes (e.g. phase
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lengthy processing times associated with sequencing. This PhD project aims to develop innovative artificial intelligence (AI) methodologies by integrating histopathology images and RNA sequencing data
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linked to exercise limitations and PEM, with the aim of improving patients' quality of life. The PhD candidate will analyze existing data from Harvard Medical School to investigate the connection between
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simulations. Job Description Are you passionate about bridging computational modeling with clinical cardiology to solve real-world healthcare challenges? We're seeking a PhD candidate to develop innovative
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for medical imaging, tailored for deep learning. The high-level goal of the project is simple: to use anatomical knowledge and existing knowledge as training data for deep neural networks (instead of manual