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Field
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, mathematics, engineering, natural sciences or other data science/machine learning/AI related disciplines Language requirements English C1 or equivalent Application deadline January, please see website for exact
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research or project activities involving machine learning or data-driven modelling you demonstrate knowledge of energy systems, smart grids, or cyber-physical systems Personal characteristics To complete a
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stage. 3. Preferential Factors Proven experience with decision support systems based on knowledge bases and machine learning. Previous experience in machine learning applied to dynamic systems or orbital
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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 Distributed machine learning takes advantage of communication and
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be duly proven at the time of hiring. 2; 3. Preferred requirements: Experience using Machine Learning algorithms. In-depth knowledge of Python and PyTorch. Previous experience collaborating
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growth methodology based on real-time growth monitoring enabled by advanced in situ characterization tools (RHEED, ellipsometry, curvature measurements, flux monitoring), coupled with machine-learning (ML
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C644914747-0000023 funded by funded by Recovery and Resilience Plan (RRP) https://recuperarportugal.gov.pt/ and Next Generation EU European Funds Application submission from 20-Feb to 06-Mar-2026 WHO WE
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Project description Electromagnetic (EM) sensing is emerging as a powerful enabling technology for modern high-value manufacturing. Advances in computing power and machine learning now allow us to
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datasets with machine learning methods, and software development are beneficial Good organisational skills and ability to work systematically, independently and collaboratively Effective communication skills
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factors: Prior experience in developing algorithms for biomedical image processing (especially aligned with the research group's areas) and machine learning/deep learning techniques. Prior knowledge of data