90 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" positions in Denmark
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Dynamics, Bioprocess engineering, Data Science, Machine Learning, Computational Chemistry Offer Description MSCA Doctoral Network machinE LEarning for inteGrated and multi-parAmetric eNzyme and bioproCess
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Interaction / Human-Centred Artificial Intelligence Help shape the future of work. This PhD project investigates how collaborative AI agents can support communication, learning, and shared understanding in blue
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machine-learning scripts that feed into these pipelines. You execute and monitor these scripts, then integrate their output into project datasets. Throughout this work, you maintain clear documentation
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in statistical and computational methods including machine learning to advance our understanding, treatment, and prevention of human disease. The Centre will be anchored at Aarhus University with hub
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inverters to enhance grid flexibility, reliability and stability. • Apply machine learning and AI tools for the battery system health estimation and maintenance prediction and integrate analytics
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. You are driven by scientific curiosity, enjoy working with complex multi-physics models, and are eager to advance probabilistic methods, machine learning tools, and simulation techniques. If you thrive
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within mathematics, data science, computer science, and computer engineering, including artificial intelligence (AI), machine learning, internet of things (IoT), chip design, cybersecurity, human-computer
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Interaction venues. For further information about the project, see: https://www.nordforsk.org/projects/nordic-perspectives-collaborative-ai-blue-collar-work-cai-blue. Your competencies You must hold a master’s
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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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written and spoken Willingness to engage in interdisciplinary collaboration and fieldwork Advantageous: Knowledge of bat ecology and species identification Experience with machine learning or automated