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Competencies Knowledge in relevant scientific field. Knowledge of research techniques or methods relevant to the lab (e.g. Microscope imaging, image and data analyses, which includes writing/modifying computer
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members work in the department. The department has a strong connection with other departments of Linnaeus University and industrial and public partners. Subject area for the position: Computer and
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Center is looking for an experienced Interventional Procedure Registered Nurse to join our Radiology team. The Radiology department at Harborview is staffed 24 x 7 and performs a high volume of image
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Job Description Harborview Medical Center - RADIOLOGY has an outstanding opportunity for IMAGING TECHNOLOGIST - SUPERVISOR. WORK SCHEDULE 1.0 FTE; FULL-TIME DEPARTMENT DESCRIPTION Advanced
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all aspects of the MRI imaging functions, and providing scientific training to MRI users regarding data acquisition, processing and analysis. Support staff, including an experienced technical director
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, through open data, open code, open educational resources and practices that support replication. Desirable: F1 Experience of ultrasound imaging research systems either relating to their operation or
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University of North Carolina at Charlotte | Charlotte, North Carolina | United States | about 10 hours ago
eligible for telework schedule of 1-2 days per week once onboarding is complete and with supervisor approval. Primary Purpose of Position This position audits/processes purchase order invoices from all
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of a vision transformer, U-Net architecture, or Diffusion model that you trained yourself. Projects in computer vision for microscopy image analysis are especially relevant. Include a link to a code
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. Postdoctoral researchers will have access to state-of-the-art imaging and cellular biology platforms, as well as a dynamic international research environment. Where to apply Website https://emploi.cnrs.fr
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:this project pioneers a new paradigm of General Genome Interpretation (GenGI) models by combining DNA Large Language Models (DLLMs) with Deep Neural Networks to predict human phenotypes directly from Whole Exome