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is currently limited. As a PhD student, you will work on the Novo Nordisk Foundation NERD-funded project aimed at developing innovativechemical tools that will enable precise elucidation of roles
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applications Co-integration of SSM-SNN cores with RISC-V processors in CMOS Hybrid analog/digital interfaces for spike generation and propagation Event-based communication protocols for ultra-low-power operation
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) at the Research Unit of Obstetrics and Gynecology, Department of Clinical Research, University of Southern Denmark (SDU), from 1 March 2026. Research environment The PhD position is part of the FEMME project funded
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, ultimately for use in health science. The goal of this PhD project is to expand on these computational methods and their formal foundations and to create efficient algorithms and implementations of them. We
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? We invite applications for a PhD position, focusing on the design and implementation of Spiking Neural Networks (SNNs) using CMOS technology. Project Overview This PhD position is part of a
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Job Description Center for Industrial Software, part of the Maersk Mc-Kinney Moller Institute, University of Southern Denmark, located in Sønderborg, invites applications for a 3-year PhD position
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three years with an expected starting date of April 1, 2026, or as soon as possible. MCI is a part of the University of Southern Denmark (SDU) and covers research and education, including applications
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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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. The hired candidates will be part of the section of Artificial Intelligence, Cybersecurity, and Programming Languages (ACP), an ambitious group that fosters collaboration, research excellence, and quality
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Digitalisation. The candidates will be responsible for researching the field of Supply chain operations analytics, more specifically focusing on understanding and assessing the role of agentic AI for supply chain