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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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-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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Position in XAI with Commonsense Knowledge for Robotics and Computer Vision 2. PhD Position in Sustainable AI for Enhancing Health Informatics (Please scroll down to read more about the project descriptions
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available scientific output (e.g., a conference poster or paper) Shortlisting may be used in the assessment process. Further information about the PhD-study can be found at the homepage of the University
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. Application procedure Before applying the candidates are advised to read the Faculty information for prospective PhD students and the SDU information on how to apply . Assessment of the candidates is based
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diplomas, Bachelor as well as Master’s degree, including transcript of notes/grades. Shortlisting may be used in the assessment process. Incomplete applications and applications received after the deadline
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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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@sdu.dk. Application procedure Before applying the candidates are advised to read the Faculty information for prospective PhD students and the SDU information on how to apply . Assessment of the candidates
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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