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an extended campus in North Little Rock and offers as well as online courses. With the addition of the Arkansas Research and Education Optical Network (ARE-ON), students can engage in information exchange with
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conditions for you to complete your doctoral degree: The opportunity to work with world class technical equipment and infrastructure, innovative software technologies, and fascinating scientific data
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organizational and documentation skills Working knowledge of Microsoft Office (Word and Excel) Excellent written communication Technically capable with ability to quickly become familiar with hardware, software
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revenue, and advancement/gift income · Familiar with CU procurement and accounting software such as Concur and Marketplace systems · Familiar with Smartsheet software or intermediate-level Excel
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/) seeks a Research Assistant I to become a member of the laboratory team. The Laboratory is interested in the gene regulatory networks that control organ development and adult organ homeostasis. We
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direction, independently and within a team environment to meet deadlines Computer skills: Word, Excel, power point, data software etc. Expectations for all UBC employees: - Willingness to respect diverse
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-methods methodologies and common software (Nvivo, STATA/SPSS, Covidence). Due to the sensitive nature of the research, the successful candidate will be subject to a Disclosure and Barring Service (DBS
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Midlands Graduate School Doctoral Training Partnership | Loughborough, England | United Kingdom | about 1 month ago
property regimes, governance structures, and environmental conditions that define those places — profoundly influence our capacity to lead active, healthy, and socially connected lives. Housing is not a
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Midlands Graduate School Doctoral Training Partnership | Warwick, England | United Kingdom | about 1 month ago
identified. The project is collaborative and interdisciplinary, combining criminological, sociological, and data-analytic approaches. While the overall direction of the research is defined, the successful
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instances to solve new, yet similar, instances more efficiently than with general purpose algorithms such as Netwon`s method. In particular, we aim to develop a neural network architecture that will allow us