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California State University, San Bernardino | San Bernardino, California | United States | 10 days ago
marketing trends and best practices. - Assist to track and report key performance metrics for digital marketing campaigns - Organize and maintain digital content libraries, including images, videos, graphics
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Responsibilities: Upload and maintain digital assets (images, documents, etc.), create and correct metadata and transcriptions, ensure quality digitization, and troubleshoot issues in digital systems. Assist patrons
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original social security card. A current passport can be used instead of the former items. This cannot be a copy, picture, PDF, on your phone or a facsimile. Only an original document. 3. You will need
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may be directly or indirectly pertinent to completing a clinical request Receive, validate, and process all external imaging for DFCI providers/satellite sites/pediatrics/Mammography Van (CD/DVD, USB
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including gathering additional supplies or equipment for them, taking x-rays using digital imaging, pouring and trimming dental impressions, and performing 4 handed dentistry. Other responsibilities will
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-graduate clinical experience in small animal diagnostic imaging. ** For more information on which English language examinations are required by the RCVS please see https://www.rcvs.org.uk/registration
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development and execution of regional marketing strategies, campaigns, and activities for Business to Business (B2B) and Business to Consumer (B2C) customers, and oversees our brand image, public relations and
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input to the project monograph. Present findings at academic conferences, project workshops and policy events. Contribute to digital dissemination, including short-form video explainers, the project
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, including pinning, pointing, spreading and labelling specimens. Preferred Qualifications: MSc in biology with specialization in insect systematics; expertise in digitally imaging insect specimens with cell
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development of 3D digital histopathology by X-ray phase contrast micro-CT Development of image processing and ML tools and models for the automated identification and quantification of clinically relevant