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polar orbit, passing near the poles about 15 times per day and regularly observing the CIFAR study region. Its payload - two optical cameras, a thermal camera, and onboard machine-learning capabilities
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following thematic areas: • AREA 1: Machine learning and AI-driven methods for design, simulation, and optimisation in architectural and construction engineering. • AREA 2: Robotic and additive
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analysis and biomedical data analysis, with demonstrated experience in organ segmentation from medical images, using both traditional and machine learning–based methods, and creation of large segmentation
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(see http://orcid.org/ ) Teaching portfolio including documentation of teaching experience Academic Diplomas (MSc/PhD) You can learn more about the recruitment process here . Applications received after
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of extrusion systems, reinforcement strategies, construction detailing, and construction scale experiments. RA3) Machine Learning and Optimisation for Digital Construction: Data-driven and simulation-based
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Superior Técnico, Portugal and 27 associated partners (from 10 countries) Format: double PhD degree, granted by two universities in Europe; see the list of main partners: https://www.eu4greenfielddata.eu
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, including artificial intelligence (AI), machine learning, internet of things (IoT), chip design, cybersecurity, human-computer interaction, social networks, fairness, and data ethics. Our research is rooted
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PhD position in Human-Computer Interaction / Human-Centred Artificial Intelligence Help shape the future of work. This PhD project investigates how collaborative AI agents can support communication
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, integrative systems biology, and machine learning. Our research is focused on analyses of data generated within the biological, biomedical, biotechnological and life sciences areas. The section has extended