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implement a hyperspectral imaging system tailored to bulk forensic trace analysis and develop chemometric and machine-learning models for material identification and classification. You will evaluate
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calls. New research areas may be added until the application deadline. Beyond the research conducted during the PhD project, a successful candidate is expected to teach three to four hours weekly during
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, and machine-learned force fields to describe ion transport and interfacial evolution. These models will be extended to mesoscopic and continuum scales (kinetic Monte Carlo, phase-field) to capture
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, statistics, data science, and public health. The goal is to develop new methods that allow researchers to learn from sensitive health data without compromising individual privacy. Using unique, nationwide
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. Learn more about the department on our website and in our research portal . Your work tasks This PhD stipend will be affiliated with a research and innovation project focusing on health system innovation
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or more subject areas. Aalborg University applies a problem-based learning (PBL) approach. Documented experience with PBL (such as project supervision, facilitation of group processes, and development
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strengthen your profile but is not a requirement for the position. The core academic profile sought is within process engineering or a related discipline. You should have an interest in and motivation to learn
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innovation, knowledge sharing, and professional development. Learn more about AAU Energy at www.energy.aau.dk. How to apply Your application must include the following: Application, stating reasons
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conducted as engaged scholarship, where research findings are developed in close dialogue with practice and contribute to ongoing strategic conversations, reflection, and learning. The successful candidate
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project under supervision • Participate in the department’s research environment • Complete a PhD training programme • Teach at one or more of the department programmes Your main task as a PhD