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related fields. Additional optional skills and qualifications: Experience in deep learning for medical imaging. Contracting requirements: Presentation of the academic qualifications and/or diplomas
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factors: Prior experience in developing algorithms for biomedical image processing (especially aligned with the research group's areas) and machine learning/deep learning techniques. Prior knowledge of data
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, corresponding to pre-, intra-, and post-operative phases of brain surgery. The work includes data pre-processing, implementation and training of deep learning methods, and evaluation of the results. Legislation
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and qualifications: Experience in deep learning for remote sensing. Contracting requirements: Presentation of the academic qualifications and/or diplomas, if applicable. Enrolment in Master's degree in
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service performance. The following work will be performed in the scope of project 6G-VERSUS. The tasks to be performed in the context of this scholarship include: Acquire foundational knowledge, including
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compression, event-based or neuromorphic vision, signal processing, machine learning or deep learning for visual data. - Motivation for research and scientific dissemination. - Good communication skills in
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of AI machine/deep learning imagery analysis methodologies and Digital twins applied to cultural heritage assets. 8 - Location Workplace: LNEC – National Laboratory for Civil Engineering, I.P. Avenida do
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qualifications: cumulatively or alternatively: a) Experience and vocation for the design and development of large language models based on deep learning and capable of multimodal processing - information to be
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: cumulatively or alternatively: a) Experience and vocation for the design and development of large language models based on deep learning and capable of multimodal processing - information to be provided in
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of an artificial intelligence (AI) solution for the diagnosis of invasive fungal infections, using microscopy images obtained in laboratory settings with limited resources. Leveraging deep learning models such as