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A digital twin is the digital representation of a physical object, using real-world data (both real time and historical) combined with simulation or machine learning models to enhance operations and
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Are you enthusiastic about exploring the fascinating interplay between physics and mechanics? Are you interested in real world applications of metamaterials? We are delighted to open a PhD position
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particle size for further processing for the plant. Selecting and constructing machine learning-based predictive model/s linking rock properties and blasting design parameters to blasting and crushing
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to create knowledge for a better world. You will find more information about working at NTNU and the application process here. About the job For a position as a PhD Candidate, the goal is a completed doctoral
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computational mechanics, machine learning, and data analytics workflows. For more information on the facilities, a virtual tour is available. The dynamic group (>20 PGR students and Research Staff) leverages
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PhD students; multiple courses on topics such as time management, handling stress and an online learning platform with 100+ different courses; 7 weeks birth leave (partner leave) with 100% salary
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using techniques and tools from dynamical systems, complex systems and machine learning, and compare their predictions with experimental data including fMRI and EEG; to collaborate with other groups in
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before and after blasting/crushing operations. The assessment of the optimal particle size for further processing for the plant. Selecting and constructing machine learning-based predictive model/s linking
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researcher. At TU/e we challenge you to take charge of your own learning process . An excellent technical infrastructure, on-campus children's day care and sports facilities. An allowance for commuting
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expected: • to complete a PhD thesis within the official appointment duration of four years; • to perform research on computational modeling and brain simulation; • to acquire in-depth knowledge