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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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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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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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. 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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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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activity(at cortical, spinal or peripheral level) and/or bio-psycho-social behavioural assessment. Advanced signal analysis, including e.g. machine learning techniques, should used for assessment and
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opportunity to learn new analysis techniques(e.g., Matlab, Python) if relevant for the task. Write up research results in the form of journal articles. Participate in and co-arrange national and international