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TEC. 2. OBJECTIVES: The NeuroEngineering Laboratory at C-BER has extensive experience in biomedical image analysis from different clinical contexts, ranging from the analysis of motor seizures in
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must design, prototype, and evaluate a geo-distributed storage system and write its findings in a scientific paper to be submitted at a conference. As such, the work is divided into 4 key steps: 1. State
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into a highly active research team with strong international visibility in image and video compression, learning-based coding, and multimedia signal processing. This project is funded by FCT/MECI through
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Lines We welcome candidates interested in one or more of the following topics: UAVs and autonomous navigation LiDAR, RGB/multispectral imaging and data fusion 3D modelling, digital twins and real-time GIS
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 25 days ago
the nature of the project which is aimed at utilizing cutting-edge technologies, such as Brain imaging, Neurofeedback and Brain-Computer Interfaces (BCI) for neurorehabilitation, the candidate must have broad
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of the Project IWGDM/CoUDLabs - funded by INESC ID, is now available under the following conditions: OBJECTIVES | FUNCTIONS 1. Data harmonisation framework: design and prototype a pipeline to map multi-source
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receive interdisciplinary training at the interface of molecular biology and biophysics with a particular emphasis on imaging and computational analysis methods. You will be part of an international network
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|2026/859 under the scope of the Project IWGDM/CoUDLabs - funded by INESC ID, is now available under the following conditions: OBJECTIVES | FUNCTIONS 1. Data harmonisation framework: design and prototype
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value. The project involves cancer cell culture, various molecular and cell biology techniques, chromatin analysis methods, and microscopy imaging. We use a broad range of molecular, cell biology and
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 2 months ago
resolution mammography images. The model should be trained using a combination of weakly supervised learning, for images without local annotations, and fully supervised learning, for images with corresponding