83 parallel-and-distributed-computing-"Meta"-"Meta" positions at University of Southern Denmark
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senior scholars across Europe. This includes participation in six international training weeks, and international secondments with academic and non-academic partners. Requirements and programme structure
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the associate professorship is a permanent position. The positions will have employment at Campus Esbjerg and will also include occasional research- and educational tasks at our program at Campus Odense
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regardless of their background (link ) - and MEGAFiT, which aims to design, test, and evaluate a research-based teaching program in fitness and strength training for students in grades 7–9 (link ) - and
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department organization, research, and teaching, please visit the department’s website . Requirements and programme structure As a PhD Student you will follow an individual PhD plan including course work
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transcriptomics and bioimaging to study human liver biopsies and advanced, preclinical models. A combination of wet-lab and computational biology, close ties to the clinic, and a wonderful team of early career
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. The successful candidate will be asked to apply to the PhD school, Faculty of Health Sciences, SDU for enrolment as PhD student. The PhD programme will be carried out in accordance with faculty regulations and the
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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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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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Experience in mass spectrometry-based proteomics, structural biology, or CRISPR-mediated gene editing Proficiency in computational data analysis Strong communication and collaborative skills and an interest in
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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