120 parallel-computing-numerical-methods-"Simons-Foundation" positions at University of Southern Denmark
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be asked to send an application to the PhD Secretariat, Faculty of Health Sciences, to be enrolled as PhD students. The PhD programme will be carried out in accordance with Faculty regulations and the
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Job Description The Centre for Quantum Mathematics (QM) at the Department of Mathematics and Computer Science, University of Southern Denmark (SDU) invites applications for a number of 2-3 year
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and uses a wide range of experimental, theoretical and computational approaches. Active research areas include self-assembled complex systems such as biomembranes, polymers, liquid crystals, as
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researchers to attract funding for their best ideas from the EU Framework Programme for Research and Innovation – ideas that can make a decisive impact on society and contribute to better health for all
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sequencing, and genome-wide CRISPR functional screening in both mouse models and clinical samples. Working closely with computational biologists and clinicians, this interdisciplinary project offers
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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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levels. In this project, the PhD student will learn to understand and apply modern causal inference techniques such as target trial emulation, marginal structural models and G-computation to observational
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existing activities in CMOS circuit design, neuromorphic computing, cryogenic electronics, and spintronic-based computing systems. The role also contributes to Denmark’s and Europe’s strategic ambitions
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Chiara De Franco cdf@sam.sdu.dk or see the course description on the study programme website. Employment Employment is in accordance with the agreement between the Ministry of Finance and the National
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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