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areas: formal methods, machine learning. Additional knowledge and experience within the following areas are appreciated: formal verification, deep learning, dynamical systems, control theory. Excellent
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of a novel condition monitoring system. Responsibilities: Develop machine learning algorithms and methods for condition monitoring of a disruptive new main bearing technology. Analyze sensor data from
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questions, and we must critically explore the governmental, technical, and ethical challenges that arise from these pressing developments. AIM focuses on generative AI and machine learning for mental health
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critically explore the governmental, technical, and ethical challenges that arise from these pressing developments. AIM focuses on generative AI and machine learning for mental health, with a particular
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methods for assessing generative AI’s compliance to GDPR. The purpose of the position is to build Bayesian metrics for privacy preserving AI(e.g., synthetic data generation, federated learning, and privacy
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functional safety, security, quantitative performance, and exploitation of modern machine learning technology. It is the overall hypothesis of S4OS that a full integration of model checking and synthesis with
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is founded by Innovation Found Denmark. Responsibilities: In the project two main approaches are compared. One based on black/gray box machine learning methods and another one on gray/white box data
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. To overcome this challenge, neural architecture search and other ideas within the general field of automated machine learning have been proposed. We seek one or more PhD students(employed as PhD fellow if you
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environmental and heritable factors in a family tree of over 6 million Danes affect disease risk, to using machine learning on genetic and phenotypic data to define clusters of patients with different disease
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In line with the commitment to building a theoretical foundation of safe reinforcement learning, we are looking for a highly motivated and talented PhD student to join our team. The position is a