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biomass remote sensing, crop modeling, data assimilation and machine learning Supervise master thesis students For PhD students: follow training in line with the doctoral school requirements Where to apply
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strong interest in computer science (software development, machine learning techniques, etc.) is desirable. · Applicants must have a maximum of 3 years of research experience after the PhD. · Language
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on terms of employment for positions such as postdoctoral fellow, research fellow, scientific assistant and specialist candidate Preferred selection criteria Familiar with advance AI techniques like
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Types Using Machine Learning Based on Citizen Science Audio Recordings and Satellite Imagery” (Bio-O-Ton-2). Our overarching goal is to develop and test novel machine-learning approaches for combining
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broad goals in decision making in contested and dynamic environments, multi-agent reinforcement learning, and secure and robust machine learning solutions. The ideal candidate will enjoy working in a team
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Institute for Brain, Cognition and Behaviour. You will work on studies of visual perception and decision-making. Research methods include computational modelling, brain imaging (fMRI), machine learning
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of progressive methods of detection, identification, classification and tracking of objects of different sizes, shapes and speeds of movement using elements of artificial intelligence and machine learning
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sustain a high quality externally funded research program. Preferred Qualifications: Knowledge of High performance computing, machine learning. Experience in writing research proposals. Experience in
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, towards future colliders. Cutting-edge machine learning developments for classical and quantum computational platforms are pursued in the group to benefit particle physics and beyond. Experience Candidates
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at least one of the following specializations: Language processing, language acquisition in heterogeneous contexts, sociolinguistic cognition, speech perception, multilingualism, human-machine communication