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will be part of a team of researchers responsible for the annual productivity studies by Aalborg University Business School. These studies provide data driven insights into regional productivity
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diagnostic expertise to more healthcare institutions maximize the utility of collected radiological data One of the major barriers to achieving this, is figuring out how to learn useful patterns in the data
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industrial partners. In particular, you will: Develop and validate physics-based, data-driven, or hybrid digital twins of Electrolysis systems, capturing their electrochemical, thermal, flow, and system-level
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other relevant stakeholders. The PhD student will contribute to the prototype development, feasibility test and evaluation of innovative cross-sectoral pathways and will be involved in data collection
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, computer engineering, computer science, data science, mathematical engineering, robotics, or a closely related field. The candidate should have solid mathematical and analytical skills and a strong interest
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In this PhD position, you will help design the next generation of circular plastics systems by combining hands-on polymer processing with data-driven modelling. The PhD study is a full-time, fixed
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organizational theory, the learning sciences, digital transformation, digital technologies, human-computer interaction, and related fields. Within the specific field, the PhD student will engage in both research
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modelling and computational neuroscience to human mobility behaviour; Modelling how people build and update internal representations of urban space; Integrating behavioural data with neurophysiological
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sensor data, and (iii) sophisticated fatigue analysis models combining advanced fracture mechanics with crack initiation and growth simulation. Additionally, you will explore fatigue mitigation strategies
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data. They will anticipate and adapt. They will optimize continuously. At Aalborg University, we are starting to build the scientific foundations for those systems. We are looking for a PhD researcher