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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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qualifications: MSc degree in electrical engineering, mathematical engineering, mathematics, computer science or similar; Solid mathematical and analytical skills, including signal processing, statistical learning
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analytical skills, including signal processing, statistical learning, optimization, deep learning, or information theory; Experience in programming, e.g., in C++, Python or Matlab. Qualification requirements
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PhD fellowship at the Copenhagen Center for Glycocalyx Research at the Department of Cellular and Mo
(CGR) The Copenhagen Center for Glycocalyx Research (CGR) aims to uncover the vital role of the glycocalyx, a cell surface layer of complex glycans, that integrates signals from cells and their
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Danish master’s degree (two years). Other important criteria are: Professional qualifications relevant to the PhD project Relevant work experience Previous publications The grade point average achieved
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. At that point, the terms of employment and payment will be according to the agreement between the Ministry of Finance and The Danish Confederation of Professional Associations on Academics in the State (AC). The
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with expertise in digital signal processing methods, and machine learning methods for amplitude and phase noise characterization of optical frequency combs, recovery of dual-comb measurement signals and
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student will become part of a team at DTU with expertise in digital signal processing methods, and machine learning methods for amplitude and phase noise characterization of optical frequency combs
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Programming skills in Python, R, and/or GIS tools Highly valued: Background in LiDAR point-cloud analysis and vegetation structure analysis or habitat monitoring Experience applying AI or machine learning