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of the sea, with a focus on questions related to marine protected areas About the position You will primarily work on developing and applying video-based methods for monitoring fish in protected areas and
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groups, YouTube video channels, and blogging. Place of employment: Tampere University, Finland Supervisory team: Prof. Jari Hyttinen, Prof. Mark van Gills, Dr. Narayan Subrmaniyam Starting date: March 1st
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primarily work on developing and applying video-based methods for monitoring fish in protected areas and increasing knowledge about ecosystem function. The work includes method development for AI-supported
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safety-critical domain, reducing hallucinations and improving robustness and trustworthiness are essential. This PhD targets principled ways to detect, analyze, and mitigate hallucinations in video-based
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experimental psychology and cognitive science to augment human intelligence with AI. Your experience and ambitions eligible for PhD study at Aalto University (https://into.aalto.fi/display/endoctoralsci/How
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to the perception of animacy when interacting with objects and people using videos (behaviour, fMRI, and MEG), 3) determine to what extent these brain representations and dimensions change when humans are immersed in
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. Applicants must be eligible to enroll on a PhD program at TU Dresden (see https://tu-dresden.de/ing/maschinenwesen/postgraduales/promotion?set_language=en) Candidates may apply to multiple positions offered
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must be ready to travel Applicants must be eligible to enroll on a PhD program at TU Dresden (see https://tu-dresden.de/ing/maschinenwesen/postgraduales/promotion?set_la… ) LanguagesENGLISHLevelExcellent
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. This PhD targets principled ways to detect, analyze, and mitigate hallucinations in video-based LVLMs for autonomous driving. Objectives Design, develop, and evaluate novel method(s) to detect and localize
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CIIMAR - Interdisciplinary Center of Marine and Environmental Research - Uporto | Portugal | about 2 months ago
aspects related to the research results, with a relative weight of 10% for the total score (previous evaluation with a relative weight of 90%). Candidates may be interviewed by video conference or in person