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analyses and machine learning. Some data for the project already exist, but additional data will be collected from behavioural tests on privately owned pet dogs in Sweden and abroad (Europe). Travel and time
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mimicked with in vivo models of metastasis, which provides unique opportunities to mechanistically dissect what drives the different cell states. You will link clinically relevant phenotypes to putative
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how social media influence both experienced and actual polarization. You will focus on different types of communication on social media and how that affects polarization. You will use an innovative
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, optically-pumped magnetometers, to understand how early learning develops. You will address how caregivers’ behaviour influences infants’ learning and how early differences in learning predict language and
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preferences of citizens, and the governance of decentralized energy systems. Together with 9 other PhDs at different universities in The Netherlands and researchers of universities of applied sciences, you will
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respond to different treatments. Working at the intersection of biomedical engineering, computational modeling, and clinical cardiology, you'll: Analyze comprehensive clinical data from our ongoing
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work with large-scale behavioural data sets using a range of approaches, including heritability analyses and machine learning. Some data for the project already exist, but additional data will be
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analytics (statistical models, machine learning, uncertainty quantification) to monitor and predict cycling travel conditions from various perspectives (safety, crowding, travel time, comfort, etc
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an exceptional international team with expertise in all aspects of the project. Your tasks will include: • Preparation of different EO and in-situ datasets for training a machine learning model • Development of ML
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5 Sep 2025 Job Information Organisation/Company University of Amsterdam (UvA) Research Field Educational sciences » Education Educational sciences » Learning studies Language sciences » Linguistics