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15 Jan 2026 Job Information Organisation/Company Aalborg Universitet Department The Technical Faculty of IT and Design, Department of Electronic Systems, Connectivity, Aalborg Research Field
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some of the most challenging and high-impact questions surrounding next-generation wind and wave energy systems, digital twins, and resilient structural design. We are looking for a motivated, curious
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statistical and machine learning techniques, including Bayesian inference and stochastic modelling, the project will quantify and analyse uncertainties in the design and operational performance
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The Department of Electronic Systems at The Technical Faculty of IT and Design invites applications for a PhD stipend in the field of Object-oriented edge-casting using semantic encoding within
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to take up the challenge of designing, developing and applying advanced X-ray imaging methods by combining experimental and computational approaches in physics. You will be working with laboratory X-ray
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. An individual career development plan containing research and transferable courses, international research visits, mentoring and career activities, is also a central element. Please visit https://www.interact
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in the group of Niels Engholm Henriksen (https://www.kemi.dtu.dk/english/research/physical-chemistry ). You must have a solid foundation and interests in quantum chemistry, applied mathematics
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pages. The description should briefly outline the proposed research, including the state of the art, research questions, theoretical framework, and planned methodology. A tentative timeline or work plan
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eNzyme and bioproCess dEsign), and it will focus on: Engineering monooxygenases for enhanced activity, selectivity and stability Strain engineering for high-throughput screening of enzyme libraries Setting
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Declaration of interest regarding PhD project within the field of biomarker and therapeutic targe...
translational liver research, including data analysis, experimental design, and scientific dissemination. Qualifications We are looking for a highly motivated PhD candidate with a strong interest in translational