27 computational-physics-superconductor PhD scholarships at University of Southern Denmark in Denmark
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performing tests, possibly in collaboration with clinical partners. Qualifications Applicants should hold a MSc in electronics, computer engineering, Physics, or a closely related field. Required Qualification
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Job Description Are you passionate about neuromorphic computing and hardware design? Do you want to contribute to the next generation of brain-inspired computing systems for healthcare 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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nanophotonics, and mesoscopic physics, possibly combinations of the above. The positions are funded by POLIMA DNRF funding, and the students will be supervised by Professor Christos Tserkezis and Professor Joel D
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21 Aug 2025 Job Information Organisation/Company University of Southern Denmark Department Department of Mathematics and Computer Science Research Field Computer science Researcher Profile First
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Neural Networks (SSM-SNNs). The project includes the co-design and integration of a RISC-V processor for hybrid neuromorphic computing. The research aims to develop ultra-low-power computing chips
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on conventional computing platforms such as GPUs, CPUs and TPUs. As language models become essential tools in society, there is a critical need to optimize their inference for edge and embedded systems
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, Biomedicine, or Computational Systems Biology. Experience with NGS data or single cell-sequencing analysis is required. Competence in adipose tissue biology, cell culture work or mouse physiology would be
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Job Description The Department of Mathematics and Computer Science at the University of Southern Denmark (SDU), Odense, invites applications for a fully funded PhD position in the foundations
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algorithmic aspects of cheminformatics. The position is founded by the Challenge Programme of the Novo Nordisk Foundation: “Mathematical Modelling for Microbial Community Induced Metabolic Diseases ”, led by