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At the Faculty of Engineering and Science, AAU Energy, a position as Postdoc in AI-augmented process control, is open for appointment from 01 July 2026 or soon hereafter. The duration
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operation process. Particularly, we seek to support architects to design more sustainable buildings through simulation-assisted performance feedback regarding initial design concepts. We will explore how AI
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Measurements and Data Processing as per June 1st, 2026, or as soon as possible thereafter. The position is available for a period of 1 year, with the possibility of extension. In electronic engineering, Aalborg
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processing, specimen preparation, microstructural and chemical characterization, and electrochemical performance evaluation. Depending on background and interests, the work may also involve exploring bio
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postdoctoral researchers willberecruited to workcloselyacross the two AAU departments of Sustainability and planning (PLAN) and Computer Sciences (CS). The project’smethodological PI is Associate Professor
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Postdoc – Performance requirements for biobased construction materials used in the building envelope
limit values for the use of biobased materials in construction Providing guidelines for moisture levels in relation to moisture from the building process and the use phase of buildings and material
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, and intentions and visions for the position Curriculum Vitae (CV) Diplomas (master's degree diploma and PhD diploma) List of publications, with an indication of the attached publications that you wish
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- ethnographic perspectives on legal and regulatory processes of infrastructure development - more-than-human perspectives on sustainable energy infrastructures - the valuation of infrastructure across
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. We expect applicants to hold a PhD in a relevant field such as techno-anthropology, science and technology studies, human-computer interaction, human-robot interaction, digital health, anthropology
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in electrical engineering, computer engineering, computer science, or similar. Strong background in communication systems, optimization, or machine learning for networked systems. Experience and