24 machine-learning "https:" "https:" "https:" "UCL" "UCL" "UCL" positions at Fondazione Bruno Kessler in Italy
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https://phd.fbk.eu/calls/detail/artificial-intelligence-and-machine-learning-fo… Requirements Research FieldOtherEducation LevelMaster Degree or equivalent Additional Information Work Location(s) Number
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within a Research Infrastructure? No Offer Description Modern robotics is at a pivotal point. While traditional learning-based methods have shown success in navigation and manipulation, they remain
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efficient and scalable artificial intelligence at the edge. TinyML and Edge AI have demonstrated the feasibility of embedding machine learning models on such devices. Still, many challenges are ahead
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predictive machine-learning models from heterogeneous data. DSIP is actively collaborating with industrial partners and research organizations. DSIP is involved in developing Deep Learning solutions for time
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segmentation, target detection and change detection along and across multiannual series of data. Methodologies like foundational models, machine learning, deep learning, multitask learning, enforcement learning
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of their behavior. A particular focus of the thesis will be on the design and monitoring of collective systems populated by AI generative agents, and on improving their theory of mind, lifelong learning and social
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methods, complemented by simulations of beta-decay chains relevant to post-fission energy release. Neural networks and other machine learning techniques will accelerate the discovery of radiation-resistant
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machine translation, and emerging agentic and interactive multimodal NLP systems involving human-AI collaboration present frontier evaluation challenges. The ultimate goal is to develop evaluation
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techniques such as cross-domain alignment, robust representation learning, and embodiment-agnostic architectures. The goal is to create robot learning frameworks that can reliably transfer knowledge across
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methodologies — including gamification strategies, adaptive interfaces, explainable AI techniques, and personalized interaction models — to support incremental learning, long-term engagement, and responsible