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electrical engineering, control engineering, applied mathematics, computer science, or a related field A strong background in probability and statistics, machine learning, or control theory Interest in cyber
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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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student projects). Qualification You should have a background within deep learning, big-data, computer vision, or related fields, as well as experience in in-line process monitoring or similar areas
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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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-experiment using advanced battery cycling machines, chambers, battery emulators, BMS-in-the-Loop, etc.) Ability to work and lead multidisciplinary research teams involving applied AI, digital twins, and
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primary tasks will be research and research-based teaching. You will teach and supervise students at Bachelor’s and Master’s level, and you will contribute to the development of the department through
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your primary tasks will be research and research-based teaching. You will teach and supervise students at Bachelor’s and Master’s level, and you will contribute to the development of the department
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, outreach and knowledge brokering activities of the Algorithms, Data and Democracy project (ADD) of which the IPA project is part (see www.algoritmer.org ). teach, supervise and examine students in Master of
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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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, and project applications. The Problem-Based Learning (PBL) approach is at the core of the teaching philosophy of Aalborg University and AAUBS, and the successful applicant will contribute to an engaging