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PhD Position on Requirements Engineering and Spec-Driven Development Faculty: Faculty of Science Department: Department of Information and Computing Sciences Hours per week: 36 to 40 Application
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PhD Studentship: Subcortical brain development and disorders, funded PhD at the University of Exeter
types in the right place at the right time to establish complex connections and functions. The dorsal midbrain, a subcortical brain region, is known to orchestrate the integration of sensory information
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, please complete the steps below. PDF versions are available here to help with planning but submissions must be made using the forms above, emailed PDFs will not be accepted. Information Session There will
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on the interests of the candidate, they may also be involved in our ongoing developments of a digital data infrastructure for 2D materials (see 2dhub.org), which would involve high-throughput electronic structure
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industry and research bodies to drive innovation across all UK manufacturing sectors, from SMEs to large global manufacturers. For details, visit the MTC website . Contact For further information on this PhD
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Element: numberavailable - Unable to display element. Data must be XMTHL compliant - Exception: XML parser error CreateXmlDoc Fatal Error: at file Integration Server line: 1 column: 1009 message
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. This research will deepen our understanding of temperature-sensitive reproduction and could ultimately guide new strategies to improve crop resilience in a warming world. For further information and to apply
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environmental data analysis - this position offers an exceptional opportunity to grow as a scientist. In RhizoTrack, you will work at the interface of microbiology, chemical ecology, and sustainable agriculture
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, copies of relevant certificates and contact information of two scientists as references to: christoph.mayerspam prevention@uni-tuebingen.de The University of Tübingen is an Equal Opportunity Employer with
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sizes and frequencies by: Measuring rock fractures from UAV data using manual and automated mapping approaches (e.g., machine learning, convolutional neural networks). Monitoring physical weathering