271 machine-learning-"https:" "https:" "https:" "https:" "https:" "UCL" "UCL" research jobs in Denmark
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in electrical engineering, computer engineering, computer science, or similar. Strong background in communication systems, optimization, or machine learning for networked systems. Experience and
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qualifications include: Ph.D. in Computer Science, Computer Engineering, Electrical Engineering or a related field; Strong background in Deep Learning (e.g., Transformers, foundation models); Strong programming
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in Computer Science, Machine Learning, Artificial Intelligence, Computational Biology, or a closely related field Has strong theoretical and practical experience in deep learning Has hands
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the Machine Learning and Artificial Intelligence. Solid mathematical and analytical skills. Knowledge about statistical machine learning, robotic perception, multimodal AI algorithms. Experience in programming
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, semiparametric inference), and ideally experience with high-dimensional econometrics, machine learning, or advanced causal inference methods. Demonstrate the ability and motivation to pursue independent research
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. Software or code development, incl. artificial intelligence and machine learning. Automation and robotics, incl. safe human-machine interaction. Serious gaming, incl. AR/VR. Life cycle analysis. You are
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and maintenance of monitoring buoys and related sensor systems. Apply image analysis and machine learning techniques to ecological datasets. Develop and implement multi-platform monitoring frameworks
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extensive experience working with large data sets in Python are required for the position. Experience with machine learning, OCR, natural language processing, geospatial analysis, and data visualization is a
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will develop atomistic models and machine-learning potentials to interpret experimental data and predict catalytic performance. The tasks can include Advancing equivariant neural network potentials
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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