73 parallel-computing-numerical-methods Postdoctoral positions at University of Washington
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                -era quantum computers to fault-tolerant/error-corrected quantum computing and simulation, and to achieve quantum advantages in fundamental physics. Our postdoctoral fellows (PDs) work with faculty 
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                candidate will have research experience with nucleic acid extraction methods and PCR assay design. This is a full-time position with a 12-month service period, with the possibility for yearly renewal 
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                imaging program involving molecular oncologists, cancer biologists, computational biologists, and imaging scientists focused on detecting breast cancer and predicting response to therapy. The position is 
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                -mediated genome editing, computational image analysis (Fiji, Python), and/or high-performance computing. Interest or experience in nontraditional research communication methods and collaborative notetaking 
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                , educators, and software engineers from I-LABS who want to bring the best methods of bilingual language teaching to early education classrooms. For this donor-funded research, the primary responsibilities 
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                disorders) populations. Our collaborative team is focusing on face-to-face interaction between children and their parents employing various methods to measure neural and behavioral responses during live 
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                and William Wilcock where they will have access to in-house petascale computing facilities and cloud computing allocations. They will interact widely with all the participants in the project and have 
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                Position Summary The Cruchaga Lab at WashU Medicine is recruiting multiple Postdoctoral Research Associates. The NeuroGenomics and Informatics Center generates and analyzes Whole-Genome Sequencing 
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                ), or biophysical/computational modeling. • Interest or experience in nontraditional research publication methods and collaborative notetaking software (e.g., Roam Research, Obsidian, Notion 
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                about exploring and applying new statistical, computational, or machine learning techniques to astronomical data sets, and extending current methodology to be applicable in the era of big data. Looking