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Field
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will be further developed by the successful candidate in collaboration with the supervisory team. Main tasks The successful candidate will: develop and evaluate image-classification workflows
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responsibility for courses covering the fundamentals of environmental remote sensing, remote sensing methods, geospatial data analysis, and image processing. Supervising practical exercises and projects involving
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to cancer progression. Using image-based siRNA screens, we have identified novel regulators of ER-phagy. This project aims to investigate the molecular mechanisms of ER-phagy and how this contributes
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of maturity, this technology requires to experiment a change of paradigm to guarantee a sustainable development for the years to come. One pathway to achieve this paradigm shift relies on the development
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-based techniques into an existing heterogeneous computing paradigm, and evaluate their solution e.g. on the automated guided vehicles at a partner institution. Their secondary objective will be to develop
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authorization or notification; template document provided. signed NOMIS code of conduct; template document provided. two external letters of reference for the candidate, to be e-mailed by the author
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completion of all pre-employment or background checks required for the role in terms satisfactory to the University. Also, to meet the University’s obligations under the National Higher Education Code
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University of North Carolina at Charlotte | Charlotte, North Carolina | United States | about 3 hours ago
gene activity is modulated through DNA methylation, histone modifications, and non-coding RNAs, with a primary focus on higher-order chromatin architecture. We were among the first to establish phase
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outside academia. The tasks include extensive use of optical diagnostics, such as: Near and far field high-speed microscopic imaging Chemiluminescence-based techniques Schlieren imaging and shadowgraphy
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a new computational paradigm that combines the versatility of the digital computer with the efficiency of close-to-physics computing. The group targets the full computational stack, from materials