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data or large data volumes in all information systems. We contribute methods and algorithms for machine learning, and data mining, including XAI, as well as for data access and query processing. Aarhus
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advanced analytical approaches, including deep learning and machine learning, to improve disease subtyping and risk prediction. You should have a strong willingness to learn, enjoy tackling challenging
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Assistant Professor in statistics for the development of privacy-enhancing techniques in health care
following areas: Synthetic data generation Machine learning Large health register data GDPR compliance rules Valued personal competencies include being independent and creative, having an outgoing personality
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focuses on the development of secure and trustworthy AI for resource-constrained embedded systems. The research will investigate how machine learning models can be designed and deployed efficiently
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intelligent control and aerial robotics for navigation in uncertain environment. You will be mainly responsible: for implementation of machine-learning algorithms for unmanned aerial vehicles; validation
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projects involve large-scale population cohorts, single-cell genomics, statistical genetics, functional genomics, machine learning, and clinical translation. We are a diverse and international team
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(satellites, drones, etc.) through AI and machine learning; 3) validation and feasibility of the introduced technologies through full-scale pilot scale, demonstration, documentation, and simulations
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) the application of remote sensing (satellites, drones, etc.) through AI and machine learning; 3) validation and feasibility of the introduced technologies through full-scale pilot scale, demonstration
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degree in computer science, mathematics, statistics, physics or relevant fields. Strong background in machine learning, preferably experience in probabilistic modeling, Bayesian machine learning, or graph
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methodological development and application of bioinformatics, biostatistics, machine learning, and data management within clinical research. CLINDA is interdisciplinary and employs biostatisticians