29 cyber-physical-system-data-mining PhD positions at University of Southern Denmark in Denmark
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Genetic Improvement of Dairy Cow Longevity, Using Large-Scale Body Weight Data from an AI-Camera System (Long Live the Dairy Cow) Applicants are invited for a PhD fellowship/scholarship at Graduate
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performing tests, possibly in collaboration with clinical partners. Qualifications Applicants should hold a MSc in electronics, computer engineering, Physics, or a closely related field. Required Qualification
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-computer interfaces, cognitive rehabilitation, and neural prosthetics. Your contributions will support the development of a custom CMOS-based SNN processor that can operate in ultra-low-power environments
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for intelligent brain-computer interfaces? We are offering a PhD position in analog/mixed-signal CMOS circuit design for EEG and wearable sensor interfaces, as part of a pioneering project focused on assistive
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-mobility, automation, climate solutions, and energy efficiency. Research at the Centre encompasses a diverse array of fields such as cyber-physical systems, mechanical structure integrity, renewable energy
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thesis). Software Architectures with a particular focus on Microservices and Distributed Systems Generative AI-driven Software Development and Maintenance Empirical Software Engineering Mining
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spanning a wide range of fields including applied cyber-physical systems, advanced mechanical systems, modelling and mechatronic prototyping. Your profile To complement our team, we are looking for one
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not be password protected. The application deadline is 29 September at 11.59 PM / 23.59 (CET/CEST) Assessment and selection process Applications will be assessed by an assessment committee
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21 Aug 2025 Job Information Organisation/Company University of Southern Denmark Department Department of Mathematics and Computer Science Research Field Computer science Researcher Profile First
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Applicants should hold a relevant MSc degree in electronics, electrical engineering, computer engineering, or related fields. Required Qualification: Solid background in digital CMOS design and deep learning