23 digital-biosignal-processing PhD positions at University of Southern Denmark in Denmark
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Job Description The Institute of Mechanical and Electrical Engineering at SDU invites applications for a PhD position in Neuromorphic Brain-Computer Interface Design. Are you a multidisciplinary
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include: CMOS-based neuron and synapse circuit design Low-power digital architecture for SNN processing On-chip learning mechanisms Integration with sensor interfaces for biomedical signal processing What
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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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is to develop an innovative digital platform to support persons with hearing problems – from initial self-help to professional care. Termed ‘Online Service Centre for heAring caRe’ (OSCAR
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Job Description The SDU Center for Energy Informatics is pleased to announce 3-year PhD positions in AI-driven decision support and digital solutions for sustainable energy and industrial systems
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that support spike-based processing and memory-efficient computation using SSMs, targeting edge-AI scenarios in wearables, robotics, or sensor networks. Research area and project description The project will co
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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
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-out key analog and mixed-signal building blocks (e.g., low-noise amplifiers, voltage/current sources, multiplexers, digital logic) for operation at cryogenic temperatures. Develop measurement setups
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and a job description for a PhD fellowship, as well as a descriptions of the assessment and hiring processes at the Department of Political Science and Public Management, please consult the department’s
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for resilient high-mix low-volume manufacturing. The aim of this PhD project is to enable fast setup of robot manipulators to complete advanced manufacturing tasks by the use of digital models. This should be