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, didactics and learning, with approximately 240 full-time researchers, including 80 PhD students, and 4,500 Bachelor’s and Master’s degree students. The school’s activities are characterised by a high degree
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-constrained machine-learning (ML) models in simulations of turbulent flows. You are expected to contribute to research and development in data-driven methodologies for turbulence modeling in LES (i.e., wall and
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you will teach and supervise students at Bachelor’s, Master’s and PhD level and carry out research of the highest international standards in the fields covered by The TrygFonden’s Centre for Child
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skills, the ability to collaborate effectively within the team, and proactive working style are essential. The candidate should be motivated, open to learning new techniques, and capable of driving
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. These variables include cover crop growth, crop nitrogen, yield, and tillage practices. You will develop novel algorithms to integrate data-driven machine learning and process-based radiative transfer models
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engineering, data science, statistics, mathematics, physics or an adjacent subject, with focus on medical image analysis and/or deep learning. Furthermore, the following competences will be expected
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operational environments Architecting and implementing AI autoencoders (e.g., TensorFlow Lite) for intelligent sensor data feature learning Taking ownership of secure data concentrator system design that