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Field
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laser repair system that integrates corrosion assessment, cleaning, cutting, repair, and painting within a single robotic unit. Using computer vision, machine learning, and predictive models, it enables
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, LiDAR ) and minimal experience of five years with SAR remote sensing (Sentinel-1; ALOS-PALSAR and NISAR); - Experience in forest modeling; - Experience in machine learning algorithms, inference
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: Design, implementation, validation, and evaluation of Artificial Intelligence and Machine Learning models for UAS identification and classification based on AI and RF spectrum occupancy data sets
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(AutoML) platform to output Machine Learning/Deep Larning models focused on image analysis. In this sense, the focus will be the development of several modules: a module to load, process and store images
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computer vision to analyze photos and thermal images. Objectives include data collection, improving available degradation models, new machine learning-based classification and risk assessment methods, and
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27 Feb 2026 Job Information Organisation/Company University of Minho Department Algoritmi Center Research Field Engineering » Electronic engineering Engineering » Computer engineering Researcher
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and might include a component of machine learning to speed up interpretation of the phage testing. The appointed candidate will be able to receive further technical guidance and supervisory support from
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of mathematics, machine learning, proficiency in programming languages including Python, C/C++. Experience with machine learning. Excellent academic background. 5. EVALUATION OF APPLICATIONS AND SELECTION PROCESS
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 2 months ago
establish reference performance and guide the design of more advanced models. The core of the work will then focus on developing and evaluating machine-learning-based NILM methods tailored
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 3 months ago
or territorial studies. Preference will be given to candidates with aptitude for working in disaster risk management environments supported with GIS and Machine Learning, basic programming skills (e.g., Python, R