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of Information Technology and Electrical Engineering. Knowledge of fundamentals of C++ programming. Competence in code optimization. Knowledge of hardware/software co-design principles, and computer architectures. Good
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. Deep Learning techniques, Data Engineering, and Semantic Technologies Open-source artificial intelligence, machine learning, statistical estimation methods, software tools, and big-data frameworks
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or machine learning frameworks Good oral and written presentation skills in a Scandinavian language at level A2 or higher Personal characteristics To complete a doctoral degree (PhD), it is important that you
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mechanics and AI. This project will advance precision medicine through collaboration with experts in cardiology and machine learning. The mitral valve (MV) ensures one-way blood flow between the left atrium
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methods to be considered for numerical optimization by an Energy and Emission Management System (EEMS). Data-driven AI methods (e.g. Reinforcement Learning and/or Recurrent Neural Networks) to be considered
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experiences and skills will be emphasized: Desired knowledge/experiences in: Working with diverse remote sensing data Data science topics particularly machine learning and deep learning. High Performance
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Applied ecology PhD: Large carnivores in Scandinavia from individual movement to population dynamics
3 Feb 2025 Job Information Organisation/Company Norwegian University of Life Sciences (NMBU) Research Field Mathematics » Statistics Researcher Profile First Stage Researcher (R1) Positions PhD
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machine learning models Experience in X-ray or electron-based materials characterization methods Personal characteristics To complete a doctoral degree (PhD), it is important that you are able to: Willing
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increasingly large amounts of data to monitor and potentially enhance performance across various facets of their business, there is a growing need for methods that automate data analysis and subsequent decision
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6 Mar 2025 Job Information Organisation/Company NTNU Norwegian University of Science and Technology Department Department of Energy and Process Engineering Research Field Engineering » Mechanical