68 machine-learning-"https:"-"https:"-"https:"-"https:"-"RAEGE-Az" positions at Aalborg University
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have: A relevant PhD degree (e.g., NLP, AI, ML, Security, Cryptography, or a related field) A relevant MSc degree (e.g., Computer Science, Software Engineering, Machine Learning, Artificial Intelligence
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: • Develop AI-driven control strategies for grid-forming inverters to enhance grid flexibility, reliability and stability. • Apply machine learning and AI tools for the battery system health estimation
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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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for collaborative learning will be open for appointment as 1st of July 2026. The employment will be a fixed term (3 years), full-time position, which will include both research and teaching activities. Your work
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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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of student projects and participation in courses related to human-computer interaction and software engineering. Your competencies Applicants should have a strong interest in human-robot interaction and the
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requirements, including link budgets, beam steering, and orbital pointing dynamics. • Experience with optimization methods and physics-informed machine learning. • A strong publication record in antennas