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reproduction/intersectional approaches Conducting quantitative analyses using computational/digital humanities/statistical methods Presenting your research at conferences Publishing findings both as co-authored
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to understanding and designing AI-supported collaborative learning environments and technologies. The lab investigates how students learn with, through, and around AI, and develops new human-AI-human interaction
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PhD Candidate to conduct research on Artificial Intelligence for managing Shipbuilding Supply Chains
the principles of the State Employees Act , and Export control (legislation that regulates the export of knowledge, technology and services). Candidates who, after assessment of the application and attachments
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commitment to equality, diversity and inclusion and an understanding of the University's Equality Act and public sector equality responsibilities. Please note applicants must be eligible and willing
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Research Fellow in Human Geography and Sustainable Development at the Department of Geography. The position is for a fixed-term period of 4 years, of which 25% will be dedicated to teaching, supervision and
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reliable and accountable, such as uncertainty quantification, interpretability, alignment, monitoring and human oversight, taking into account relevant standards and regulation, including the EU AI Act
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Max Planck Institute for Biological Cybernetics, Tübingen | Bingen am Rhein, Rheinland Pfalz | Germany | 26 days ago
interacts with the prefrontal cortex to integrate interoceptive signals and guide higher-order cognition. Combining ultra-high-field layer fMRI at 9.4 Tesla, diffusion MRI, and machine learning in humans with
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like you? You hold an MSc degree in Human Movement Sciences, Neuroscience, Biomedical Engineering, Technical Medicine, Biomedical Sciences, Medicine, or a related field, and have a strong interest in
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Are you passionate about human behavior, XR technology, and real societal impact? Join us in studying how people interact with complex environments and empowering individuals with disabilities with
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. These differences introduce distribution shifts that can degrade model performance and reliability over time, particularly in “one-to-many” supervision settings where a single human operator oversees multiple agents