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Field
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Biomechanical Engineering, biomedical engineering, technical medicine, or a related field. Strong interest in musculoskeletal modelling, human experimentation, and medical imaging. Solid programming skills (e.g
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candidate you will: Collaborate closely with the experimental team that acquires these multiscale data Analyse rat MRI data, including integration with histology and calcium imaging Combine data across
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of brain imaging and contribute to insights that can improve healthcare practice. Technical PhD Candidate In this role, you will be responsible for developing and refining MRI technologies to visualize brain
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rehabilitation center, and will be embedded in the Vision and Imaging Data Analytics group at the Department of Intelligent Systems and Centre for Cognitive Science and Artificial Intelligence at Tilburg
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experiments as well as bioinformatics and advanced imaging techniques. Your core tasks are: Cloning and expressing recombinant proteins. Developing and optimizing purification protocols. Designing and
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Unravel the complexity of valve disease in heart failure using Digital Twin technology. Help transform how cardiologists decide when and how to treat patients through personalized computer
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master’s degree in a relevant field (e.g., cognitive neuroscience, biomedical engineering, biological psychology) experience with programming (e.g., MATLAB, Python) hands-on experience with neuroscientific
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motivated, you have a collaborative and persevering mindset and a keen interest in memory research. a master’s degree in a relevant field (e.g., cognitive neuroscience, biomedical engineering, biological
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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
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, Biomedical Sciences, Molecular Sciences, Nanobiology). Experience with the basal transcription process, DNA damage response or with live cell imaging and microscopic data analysis is an advantage but not