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-disciplinary team of researchers, including bioinformaticians, pathologists, oncologists, and computer scientists, and conduct original research on computational pathology. Digital pathology images contain rich
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their work through cataloging and documentation, preventive care, processing loans, storage, and facilitation of storage and object access, while receiving hands-on training in professional collection
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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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to solve this issue. Indeed, there is growing evidence that thermal imaging could serve as a tool for measuring emotions in a non-invasive, contact-free way, that does not require verbal communication
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of manufacturing. We have identified an opportunity to combine continuous microfluidic (µF) process models, process analytical techn ology (PAT) and machine learning (ML) to achieve a paradigm shift in bioprocess
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6 Nov 2025 Job Information Organisation/Company INESC ID Research Field Engineering » Computer engineering Researcher Profile First Stage Researcher (R1) Positions Master Positions Country Portugal
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Instituto de Investigação e Inovação em Saúde da Universidade do Porto (i3S) | Portugal | 12 days ago
the recording of dendritic electrical signals using electrophysiological and imaging techniques. The fellow will be involved in setting the protocol for imaging voltage signals in dendrites of pyramidal
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. Proficiency in programming languages like C and Python, as well as deep learning frameworks such as PyTorch and TensorFlow. Knowledge in imaging and computing device and equipment. Strong communication
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performance. The project will leverage one-of-a-kind in-process imaging data to gain unparalleled insights into the laminate microstructure. The outcome of this work will be a predictive capability to quantify
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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