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mechanisms and kinetics to stabilize highly active but metastable surface motifs sustainable catalytic processes. Modeling Atomic Processes on Nanoparticles Develop atomistic models and machine-learning
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mathematics, or a related field. The candidates for the PhD position will be assessed on the following criteria: Strong skills in probabilistic modelling, machine learning, or simulation techniques. Programming
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mechanisms and kinetics to stabilize highly active but metastable surface motifs sustainable catalytic processes. Modeling Atomic Processes on Nanoparticles Develop atomistic models and machine-learning
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algorithmic solution development. The group focuses particularly on automated decision-making in autonomous cyber-physical systems, combining mathematical optimization, machine learning, and decision theory
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. Mathematical skills: Competence in mathematical modeling of dynamic systems and probabilistic frameworks. Experience with machine learning or AI methods for localization or perception (e.g. learning-based SLAM
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of student projects and participation in courses related to human-computer interaction and software engineering. Your competencies Applicants should have a strong interest in human-robot interaction and the
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Job Description These days, the inner workings of molecules and materials can be probed and modelled by advanced simulation tools on modern computer architectures. However, the routine applications
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problem-based learning, with a focus on interdisciplinary collaboration between academia and industry to generate solutions to practical challenges within the sector. Part of the project’s outcomes will
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applicants to hold a Master’s degree in a relevant field such as techno-anthropology, science and technology studies, human-computer interaction, digital health, design, anthropology, sociology, or related
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% of all employees are internationals. In total, it has more than 600 students in its BSc and MSc programs, which are based on AAU's problem-based learning model. The department leverages its unique