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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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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
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paradigms that support collaborative processes rather than isolated individual use. Combining perspectives from the learning sciences, Computer-Supported Collaborative Learning (CSCL), Computer-Supported
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paradigms that support collaborative processes rather than isolated individual use. Combining perspectives from the learning sciences, Computer-Supported Collaborative Learning (CSCL), Computer-Supported
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data sources (e.g., registry data, surveys, and organisations). Your competencies Digital methods such as machine learning based classification, computational text analysis, network analysis, web
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. This includes working with soil physical properties and soil characterization in the field and laboratory, integrating monitoring data, and combining different data sources into coherent model setups. You will