41 machine-learning "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" "UCL" PhD positions at Aalborg University in Denmark
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PhD from the University of Nantes in France. He has worked 10 years at the university of Aalborg focusing on the development of statistical methodology for application in machine learning and
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candidate is expected to hold: A master degree in biomedical engineering or computer science, Excellent programming skills (Python). Experience with data curation, large-scale datasets, and machine learning
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electrical energy storage systems; energy management systems. Experience with data processing, statistical analysis and machine learning techniques is an advantage. Knowledge with Mathworks suite, C/C++ and
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of these materials. Implementation of artificial intelligence (AI) and machine learning (ML) to establish the connection between the existing models and material data (both literature and the baseline established in
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% of all employees are internationals. In total, it has more than 600 students in its BSc and MSc programs, which are based on AAU's problem-based learning model. The department leverages its unique
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for spinal surgery. The Candidates for this stipend should have a background in software engineering or similar and have substantial experience with machine learning. All cases involve various degrees of image
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algorithmic solution development. The group focuses particularly on automated decision-making in autonomous cyber-physical systems, combining mathematical optimization, machine learning, and decision theory
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. Mathematical skills: Competence in mathematical modeling of dynamic systems and probabilistic frameworks. Experience with machine learning or AI methods for localization or perception (e.g. learning-based SLAM
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% of all employees are internationals. In total, it has more than 600 students in its BSc and MSc programs, which are based on AAU's problem-based learning model. The department leverages its unique
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properties through computer simulations. The project also includes validation of materials in the lab and translating the findings into practical recommendations for use in real power-electronics environments