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control in neuronal synapses You will be working with primary neuron cultures, rodent in vivo models, and patient brain biopsies You will use advanced microscopy for super-resolution and live imaging
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biomedical image and signal processing; Previous experience in computer vision; Minimum requirements: Degree in Computer Science, Informatics Engineering, Data Science, Bioengineering or Applied Mathematics
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of manufacturing. We have identified an opportunity to combine continuous microfluidic (µF) process models, process analytical technology (PAT) and machine learning (ML) to achieve a paradigm shift in bioprocess
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welcome to apply. Familiarity with image data analysis tools such as SPM, FSL, AFNI, and/or DSIStudio etc will be an advantage. Signal processing and programming skills (e.g. with Matlab, Python) will be
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Technology (RBI-FCT), by the Research Fellow Statute (EBI), by the Norms for Grant Assignment and Management within R&D Projects, by the Code of Administrative Procedure (CPA), all in their current wording
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imaging system for immunology. A novel, rapid AAV-mediated technology for generating transgenic mouse models. Comprehensive core facilities for advanced flow cytometry, genomics, and single-cell sequencing
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of Biomedical Engineering (SBME). The successful candidate will work on advanced machine learning applications in computational pathology, medical imaging, and clinical text analysis. They will be expected
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looking for research engineers with the following backgrounds: Medical Imaging Medical time-series analysis Foundational Models Medical AI New Learning Paradigms Representation Learning The collaborating
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Engineering, Biomedical Engineering (Medical Informatics), or related areas. Recipient category: Masters, enrolled in the course: Degree courses: enrolled in doctorate. Non-conferring degrees courses: enrolled
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heart. These new therapeutics will be used to treat MI patients, enabling regeneration of cardiac muscle to reverse heart failure and save lives. Heart failure is incurable, irreversible and a leading