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experience technical problems, please contact hcm-support@sdu.dk. Application procedure Applicants are advised to read the SDU information on how to apply . Assessment of the candidates is based
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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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files. All pdf-files must be unlocked and allow binding and may not be password protected. The assessment process Applications will be assessed by an assessment committee and the applicant will receive
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in the fields of Biochemistry and Bioengineering with focus on biochemical processes in agricultural wastes and molecular level solutions to mitigate pollutions and emissions from agriculture. The main
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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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fields: Mechanical product development Integration of Computer Aided Design and Computer Aided Manufacturing in product development Finite Element Analysis of mechanical structures including joints and
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or more of the following fields within mechanical engineering: Material characterization, employing several measurement apparatuses like e.g. SEM or optical microscopy Material manufacturing processes
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the Center for Pharmaceutical Data Science Education Support leadership and act as an administrative contact for stakeholders at SDU and the University of Copenhagen (KU) Ensure processes align with SDU
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responsible for the development, maintenance, and oversight of CPop’s data systems. You will ensure that data processes are secure, efficient, and compliant with GDPR and institutional policies, while
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for seizure detection. These algorithms will be implemented on a spiking neural network (SNN) processing unit deployed on FPGA and custom-designed chips with an integrated detection mechanism. Research area and