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experience and profile: • PhD in machine learning theory, with thesis submitted before the start of the Postdoctoral position. • Publications on machine learning theory in proceedings of international machine
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, ballistocardiography, and bio-radar) in combination with machine learning based algorithms for time series analysis into the whole OSA diagnosis and treatment pathway. During diagnosis unobtrusive sensors that can be
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investigate how machine-learning based algorithms can be used to personalize the user experience. The goal of this personalized user experience is to enable each individual user to discover their own
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Postdoctoral position on project 'Libraries as Links in Learning: Making the Meaning of Manuscripts'
Apply now Leiden University Centre for the Arts in Society (LUCAS) invites applications for a Postdoctoral positionwithin the project ‘Libraries as Links in Learning: Making the Meaning
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). The empirical research should capture and analyze teaching and learning processes, for example by video analysis or eye-tracking. Development activities for instance may include AI tools, the creation
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(Groningen), and the UK. This post-doc project offers a unique opportunity to work in an international environment and to acquire valuable research experience for someone who has recently completed a PhD in
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smart manufacturing demonstrators and digital twins into the Industrial Engineering and Management (IEM) educational programs. You will work closely with faculty, PhD/EngD students, and companies, with a
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Employment 0.8 FTE Required background PhD, Research University Degree Organizational unit Nijmegen School of Management Application deadline 03 June 2025 Apply now Are you interested in the role
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), including research project supervision and teaching of research skills. What do you have to offer A PhD in neuroscience, psychology, computer science, or a related field; Peer-reviewed publications based
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develop a simplified model focusing on the leader stage. You will: Analyze experimental data and microscopic simulations Identify relevant physical features and parameters Apply machine learning techniques