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designing, developing and evaluating systems and models to enhance learning through AI technology. The PhD fellow will engage with developing and evaluating models and agents, as well as, multi-agent networks
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(FEUP), under the scientific supervision of Professor Doctor Ana Rita Lado Teixeira Ribeiro. Grant duration: Initial duration of 4 months, with the predicted starting date in October 2025, on an exclusive
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of periodic chiral systems and improve current software limits. ii) design computational protocols to perform applications of the developed software. Expected Results: simulate, predict and rationalise
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, including designing, developing and evaluating systems and models to enhance learning through AI technology. A part of this work is also to consider opportunities for innovation related to start-up companies
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15 active researchers at the assistant, associate, and full professor levels, as well as 10 PhD and post-doc students. Our faculty members conduct and publish research on a wide range of topics
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seasonal emissions such as winter CH4 emissions, using AI tools to develop upscaling tools or upscale to circumpolar region, or using climate modeling such as the Norwegian Earth System Model to constrain
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Computer Vision There is growing trend towards explainable AI (XAI) today. Opaque-box models with deep learning (DL) offer high accuracy but are not explainable due to which there can be problems in
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the previous point and the documents proving the conditions in this Notice, namely: a) Application for Application addressed to the President of the Selection Jury (model attached); b) Copy of doctoral
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of smart technologies to visualize yard operations in a digital form (such as virtual models and digital twins). Smart technologies can collect, analyze, and represent data from various sources