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10th October 2025 Languages English English English The Department of Electronic Systems has a vacancy for a PhD Candidate in Machine Learning & Signal Processing for Industrial Applications Apply
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open up exciting career opportunities? Are you interested in cable technology and condition monitoring and do you have a strong competence in signal processing and machine learning? As a PhD candidate
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This is NTNU NTNU is a broad-based university with a technical-scientific profile and a focus in professional education. The university is located in three cities with headquarters in Trondheim. At NTNU, 9,000 employees and 43,000 students work to create knowledge for a better world. You will...
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, and hippocampus in animal and human. Students have access to cutting-edge science and infrastructure across the KISN and NTNU. Additionally, we provide opportunities for PhD students to learn essential
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distribution modelling Experience with spatial analysis and mapping tools (e.g., QGIS, ArcGIS, or spatial packages in R/Python) Interest or experience in applying AI or machine learning methods to ecological
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Cybernetics at NTNU is offering a fully funded PhD position in the area of learning-based control and decision-making for complex multi-agent systems. The project explores new computational frameworks
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19th October 2025 Languages English English English The Department of Engineering Cybernetics has a vacancy for a PhD Candidate in Learning-Based Control Apply for this job See advertisement This is
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to your work duties after employment. Required selection criteria You must have a relevant Master's degree in Computer Science, Artificial Intelligence, Data Sciecnce (with a focus on machine learning
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inference methods, survey design, and/or machine learning Experience with web scraping and API-based data collection Organizational and coordination skills, such as assisting in drafting terms of reference
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the development of headache, and how headache impacts the Norwegian economy. The project applies advanced methods in epidemiology, causal inference, genetic epidemiology, and machine learning. As a PhD candidate in