32 programming-"https:"-"https:"-"https:"-"https:"-"https:"-"https:" PhD positions at Aalborg University in Denmark
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to plan and carry out long-term empirical research tasks. You will work closely with Port of Aalborg, where you will have a second workspace, and you should be comfortable engaging with both academic and
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software and are motivated to develop and apply dynamic models of energy and chemical processes. You are familiar with programming languages and computational tools. Expertise in a particular software
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the general study programme Electrical and Electronic Engineering; as per September 1, 2026, or as soon as possible thereafter. In electronic engineering, Aalborg University is known worldwide for its high
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At the Faculty of Engineering and Science, AAU Energy, a PhD stipend position is available within the general study programme. The position is offered in relation to the research group Underwater
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of the Built Environment, Faculty of Engineering and Science, Aalborg University (Copenhagen) within the general study programme Civil Engineering. The stipend is open for appointment from October 1st, 2026
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that the candidate will be enrolled as a PhD student at the Technical Doctoral School of IT and Design in accordance with the regulations of Ministerial Order No. 1124 of September 19, 2025 on the PhD Programme at
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At the Faculty of Engineering and Science, AAU Energy, a position as PhD stipend is available within the general study program. The stipend is open for appointment from 1st September 2026 or soon
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able to plan and complete longer research tasks. At the same time, you contribute actively to the research environment, share your work in progress and engage in constructive feedback with colleagues
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a PhD student at: the Doctoral School of Engineering and Science in accordance with the regulations of Ministerial Order No. 1124 of September 19, 2025 on the PhD Programme at the Universities and
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programming (particularly Python) and modern machine learning frameworks (e.g., PyTorch, TensorFlow). An interest in AI security, trustworthy ML, or the reliability of ML systems in safety-critical settings