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Job Purpose To make a contribution to an ERC-funded project Dynamic network reconstruction of human perceptual and reward learning via multimodal data fusion, working with Prof. Marios Philiastides
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grow. We welcome you to join our community of faculty, students and alumni who are shaping the future of AI, Data Science and Computing. Key Responsibilities: Investigate how quality perception emerges
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), multimodal vision and language models, and Large Language Models. Please find prior work here: (Google Scholar: https://scholar.google.com/citations?hl=en&user=oEifmSgAAAAJ&view_op=list_works&sortby=pubdate
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qualification (usually PhD). Tasks: The successful candidate will contribute to one or more of the following focus areas: Human-Centered Design and Interaction: advance understanding of human sensory perception
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/ habilitation thesis). Tasks: The successful candidate will contribute to one or more of the following focus areas: Human-Centered Design and Interaction: advance understanding of human sensory perception, trust
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than 110.000 associates, many with a family history of AD, who actively participate in research initiatives and citizen science. This community enables large-scale studies on risk perception, biomarker
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models (NeuroAI). The computational models we work with include vision deep learning models (including topographical, recurrent, or developmentally inspired models), multimodal vision and language models
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integrated autonomous perception-decision-execution robotic systems for farm, facility, orchard, livestock/poultry, and aquaculture scenarios, aiming for accelerated breeding, precision production, and
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the Machine Learning and Artificial Intelligence. Solid mathematical and analytical skills. Knowledge about statistical machine learning, robotic perception, multimodal AI algorithms. Experience in programming
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of competitive research proposals. You should have experience in the following areas: Applied Machine Learning for Autonomous Systems: Experience developing and deploying ML models for perception, prediction