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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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technical expertise listed above, experience with teaching and supervision is expected. Familiarity Problem Based Learning concepts are welcomed. The candidate should be prepared to teach in Danish in
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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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for society. Our education is based on problem-based learning and is recognised for producing highly skilled graduates with excellent employability. We apply several pedagogical approaches, including working in
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, computer science, interaction design, applied artificial intelligence, or a related field. We welcome candidates from diverse backgrounds, demonstrating strong collaboration skills and the ability to acquire
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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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Centre for Problem-Based Learning (PBL) is at home. We create educations that are aimed at the job market and a society with increasing focus on technology, digitization, sustainability and partnerships
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are willing to learn Danish within two years. Danish language training will be provided. Contact information For further information, please contact: Dean Birgit Schiøtt, email: [email protected] , phone: +45 2982
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are motivated to learn EV and small-RNA methods are explicitly encouraged to apply. Required qualifications PhD degree in Plant Science, Plant Physiology, Plant Molecular Biology, Microbiology or a related
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Assistant Professor Position in Transient Electromagnetic Signal Processing, Modelling and Inversion
machine learning, multidimensional inversion, and probabilistic geological modelling to enable efficient mapping in previously inaccessible terrains. The successful candidate will be employed primarily in