154 machine-learning "https:" "https:" "https:" "https:" "https:" "U.S" "U.S" "U.S" PhD scholarships in Norway
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- NTNU - Norwegian University of Science and Technology
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- NORWEGIAN UNIVERSITY OF SCIENCE & TECHNOLOGY - NTNU
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universities, research institutes, industry, public agencies, and leading global institutions. We welcome motivated applicants in robotics, control, AI, machine learning, physics, and related fields, including
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areas: Developing and training robust machine learning surrogates to replace computationally expensive high-fidelity simulations, enabling exploration of vast design spaces. Formulating optimization
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with the Civil Servant Act, the Security Act, and the Export Control Act. Interested in learning more about the position? We are happy to tell you more about life on campus. Contact associate professor
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interests through elective courses and secondments. • Blended Learning Approach: Our training combines intensive in-person workshops at partner institutions with regular interactive online seminars, journal
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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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of experts? Then this job may be for you. For more information and how to apply: https://www.jobbnorge.no/en/available-jobs/job/296128/phd-fellowship-in-systems-neuroscience Where to apply Website https
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complex biological systems. Research Environment & Collaboration The successful candidate will work at the interface of machine learning and biostatistics, developing new theory, algorithms, and scalable
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into reliable information about structural and aerodynamic behaviour remains a challenge. The PhD will develop data-driven methods that combine measurements, physics-based models, and machine learning to extract
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, Sport Management, and Economics. We have about 315 employees and 3 800 students at our campuses in Molde and Kristiansund. Read more about us: https://www.himolde.no/ The PhD position is organized under
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broad range of areas, including causal inference and time-to-event analysis, clinical trials, epidemiology, high dimensional statistics, infectious disease, machine learning and mathematical modelling