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. While designed to assist, AI recommendations may inadvertently impede cognitive reasoning and steer decision-making. This raises novel questions about designing systems that assist users while supporting
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, is under threat from growing reliance on artificial intelligence (AI) technology. While designed to assist, AI recommendations may inadvertently impede cognitive reasoning and steer decision-making
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position is based at the Center for Quantitative Genetics and Genomics (QGG) under the supervision of Asst. Prof. Irene Julca. The position is offered as a two-year appointment, with the possibility
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thereafter. Explaining complex AI models is a key challenge for ethically responsible AI. Explainable AI (XAI) research aims to provide relevant information to assist developers and users in analyzing AI
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of Prof. Georg Madsen, with regular shorter research stays at Aarhus University. The project combines density functional theory (DFT), machine-learned force fields and atomistic simulations to uncover how
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working environment and place strong emphasis on good relationships between colleagues and students. We therefore seek candidates with an open, constructive, and collaborative approach. Who we
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University in the group of Prof. Thomas Vosegaard. The place of work is Gustav Wieds Vej 14, 8000 Aarhus C. Project goal and tasks We combine state-of-the-art instrumentation and experiments with modelling
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at the Department of Chemistry, Aarhus University in the group of Prof. Thomas Vosegaard. The place of work is Gustav Wieds Vej 14, 8000 Aarhus C. Project goal and tasks We combine state-of-the-art instrumentation
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total scattering, WAXS and SAXS, imaging, and femtosecond X ray diffraction to probe structure and dynamics in real time under device relevant conditions. Target facilities include DESY, MAX IV, European
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of materials and devices during switching, combining methods such as laser pump and X ray probe total scattering, WAXS and SAXS, imaging, and femtosecond X ray diffraction to probe structure and dynamics in real