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PhD positions in Human-Centred Artificial Intelligence The Department of Computer Science at Aalborg University invites applications for two fully funded PhD positions working with Professor Niels
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At the Department of Culture and Communication, Faculty of Social Sciences and Humanities, Aalborg University, a PhD Scholarship in PhD Scholarship in Implications of Artificial Intelligence and
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At the Faculty of Medicine, Department of Health Science and Technology, one or more PhD stipends in Human-Machine Interaction are available for appointment from October 1, 2026, or as soon as
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PhD Scholarship in Development of Cement-Free Living Building Materials for Sustainable Construction
for scientific staff: www.inside.dtu.dk/en/human-resources/during-employment/salary/salary-structures . The period of employment is 3 years. Starting date is 1 February 2027 or according to mutual agreement
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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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deeply characterized human cohorts. The group is embedded within CBMR's highly interdisciplinary environment and collaborates extensively with leading researchers across Europe and North America. Current
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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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are allocated to individuals who hold a Master’s degree. PhD stipends are normally for a period of 3 years. It is a prerequisite for allocation of the stipend that the candidate will be enrolled as a PhD student
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of integrating GenAI in professional design software. You will join the Human Augmentation and Collaboration research group, an active and supportive research group focused on designing and evaluating interactive
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responsible for: Conducting research on sustainable and resource-efficient AI systems for edge datacentres. Creating hardware-aware search spaces for CPUs, GPUs, and accelerators, and developing multi-objective