29 postdoc-exercise-physiology PhD positions at University of Southern Denmark in Denmark
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use. Work description The selected PhD student will be responsible for the full development of the neuromorphic BCI system. Tasks will include: Designing a 32-channel, low-power analog front-end
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This project explores the use of state-space models (SSMs) for sequence modeling in large language models (LLMs), focusing on their CMOS-based hardware implementation. The PhD candidate will develop energy
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and custom processors. Work description Investigate SSM representations compatible with spiking dynamics Investigate the usage of SSM along with sensor devices. Design digital/analog building blocks
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the factors causing a lack of GPs and explore how Denmark can improve the accessibility of general practice services for all citizens. By studying these interconnected factors, the project aims
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of Employment Employment as a PhD fellow is a 3-year salaried position and ends automatically at the conclusion of the period. The position holder may not undertake other paid work during this period. Employment
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study programme. List of publications and maximum 2 examples of relevant publications (in case you have any publications). References may be included, you're welcome to use the form for reference letter
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the graduation class for the study programme. References may also be includes, you're welcome to use the form for reference letter at the Faculty website . List of publications and maximum 2 examples of relevant
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must clearly state that the candidate has been among the top 30 pct. in the graduation class for the study programme. References may also be includes, you're welcome to use the form for reference letter
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Job Description Are you passionate about designing ultra-low-power electronics for neural and wearable systems? Do you want to develop custom CMOS circuits that serve as the foundation
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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