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- NTNU Norwegian University of Science and Technology
- NTNU - Norwegian University of Science and Technology
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Field
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++ and Python. Experience with ROS is a plus Extensive hands-on/practical experience on developing, implementing and/or testing robotic systems Personal characteristics To complete a doctoral degree (PhD
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selection criteria Experience with AI / probabilistic AI / Machine Learning / Reinforcement Learning Experience with numerical optimization and MPC Strong programming skills (Python, C) Personal
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Experience with AI / probabilistic AI / Machine Learning Experience with numerical optimization and MPC Strong programming skills (Python, C) Experience with predictive maintenance, fatigue, fault detection
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metrics directly into the design loop to drive durable, resource-efficient components, validated against analytical benchmarks or experimental data. Where to apply Website https://www.jobbnorge.no/en
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affiliated with the Centre, and opportunities for research stays with partners, both nationally and abroad, through its international network. Read more about the Centre and its research at the website: https
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criteria Strong skills in relevant programming languages, particularly python Knowledge of, and experience from, the maritime industry is an advantage Knowledge of generative models, reinforcement learning
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knowledge for a better world. You will find more information about working at NTNU and the application process here. About the position The Structural Mechanics group (https://www.ntnu.edu/kt/research/sm ) is
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statistical modelling are essential for this position. Demonstrated strong proficiency in programming (e.g., Python, PyTorch/JAX, or similar) and computational skills are required for this position. Candidates
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affiliated with the Centre, and opportunities for research stays with partners, both nationally and abroad, through its international network. Read more about the Centre and its research at the website: https
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until obtaining a PhD Carry out research of good quality within the framework described above Academic publications and popular science dissemination Participate in the research group SIMLab (https