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Instituto de Ciência e Inovação em Engenharia Mecânica e Engenharia Industrial | Portugal | 3 months ago
to accelerate technological maturity (TRL), validation, and the transfer of scientific results. Main Responsibilities: Application of advanced Machine Learning, Deep Learning, reduced-order models, and physics
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learning and deep learning applied to electroencephalography in the context of brain-computer interfaces, including experience with MATLAB and Python and in the design and conduct of experimental studies
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machine learning). Minimum requirements: Average grade of 18 in the Master Degree in Industrial Engineering and Management. Proficiency in Portuguese and English. 5. EVALUATION OF APPLICATIONS AND SELECTION
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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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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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equations, numerical analysis, mathematicalmodels in biomedicine, biostatistics, machine learning, statistical learning, multivariate statistics, time series,mathematical modelling, generalized linear models
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supporting documentation, proven experience in all of the following areas: Computer vision and video processing (ingestion, ROI, 2D/3D keypoints, heatmaps); Deep learning and temporal modelling (CNNs
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. Applications start date: September 4, 2026 Applications end date: October 4, 2026 or until the position is filled Where to apply Website https://docs.google.com/forms/d/e
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.; This solution will be fundamental to ensuring greater robustness and reliability of data-centric applications (for example, databases and machine learning tools), as well as the durability of the data processed