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, procurement, or grant administration will be an added advantage. Experience in areas such as Machine Learning, Deep Learning, Computer Vision, Large Language Models, Data Analytics, or Intelligent Systems will
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Reference Number AE2026-0230 Is the Job related to staff position within a Research Infrastructure? No Offer Description Portuguese version: https://repositorio.inesctec.pt/editais/pt/AE2026-0230.pdf CALL FOR
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15 Jul 2026 Job Information Organisation/Company INESC TEC Research Field Computer science Engineering » Computer engineering Researcher Profile First Stage Researcher (R1) Application Deadline 29
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planning and identification of strings and modules in the field. Development of a computer vision and machine learning pipeline for the detection, localisation and classification of defects in photovoltaic
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with the Ganna Lab (https://www.dsgelab.org/ ) at FIMM and the Probabilistic Machine Learning Lab (https://www.helsinki.fi/en/researchgroups/probabilistic-machine-learning ; groups of Acerbi and Klami
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recognition elements. Experience applying machine learning to spectral data (Raman, LC–MS, or similar). Experience working on translational or industry-linked research projects. Where to apply Website https
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only supports your professional development, but also actively contributes to positive change in society You can expect numerous benefits , such as public transport season tickets and car sharing, a wide
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machine learning frameworks. Proficient in technical writing and system documentation. Self-directed learner with strong problem-solving and research capability. Where to apply Website https
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should possess: PhD/Ms/BSc in Computer Science, Artificial Intelligence, Electrical Engineering, or a related discipline. Strong research background in one or more of: Computer Vision Machine Learning Deep
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, selectivity and phenotype mechanisms directly in primary human cells and employ machine learning methods for data analysis. This includes activity-based profiling, global- and phosphoproteomics and phenotype