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will focus on designing and optimizing integrated reactor concepts that combine sequential catalytic reactions with in-situ separation. Using a multi-scale approach, you will couple catalyst development
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developing a new quantum sensing platform for probing correlated phases of matter at the atomic scale. The postdoctoral researcher will lead the theory component of a research program, developing microscopic
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well as providing a virtual environment to test large-scale infrastructure such as in-road charging networks and to assess the vulnerability of such systems to disruption and climate-induced weather events. The post
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scalable bioinformatics pipelines on cloud-based infrastructure. The Research Fellow will be responsible for the code base supporting the large-scale genomic processing and analysis pipelines at the SMaHT
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will join a dynamic, interdisciplinary team focusedon developing and applying novel AI and statistical methods for multi-omics data analysis. This position offers a unique opportunity to work at the
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combines research-oriented bioinformatics with scientific pipeline and software development. The selected candidate will contribute to analyses of large-scale genomics datasets and support the development
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community. More information about the School of Graduate Studies is at: http://www.sgs.utoronto.ca/Pages/default.aspx Your opportunity: Working with a dynamic team under the general direction of the Associate
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develops predictive, multi-scale computational frameworks to guide sustainable microbial food production. By coupling data science with mechanistic models, this collaboration between universities, research
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of the world's oldest medical schools. (https://www.igmm.cnrs.fr/en/ ) The Lab: The work will be carried out in the AI for Genome Interpretation (AI4GI) group, led by Dr. Daniele Raimondi. The group focuses
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 3 hours ago
ecosystem services. By synergistically combining passive/active multi-scale remote sensing data with mechanistic biogeochemical and hydrological models, this research aims to address critical knowledge gaps