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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 10 hours ago
inform observable macroscopic properties as part of the activities of the UNC Superfund Research Program (SRP) (https://sph.unc.edu/superfund-pages/srp/). This work involves running, developing, and
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opportunities for advancement. A dedication to providing outstanding diagnostic service for colleagues within the VMC, as well as for private veterinary practitioners and clients who submit diagnostic material
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within the research laboratory. This role also assists scientists, both independently and collaboratively, with laboratory and investigative procedures and may be required to work with animal models and/or
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materials, device designs, and operational modes for these bioelectronic implants. You will also develop and validate finite element models (COMSOL Multiphysics) to support the experimental work. The work is
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. Appointment Start Date: Preferably by July 2026 Group or Departmental Website: https://hph.stanford.edu/ (link is external) How to Submit Application Materials: Submit all application materials
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models that support operational analytics, strategic reporting, automation, and emerging AI-driven insights. This role is critical to enabling data-informed decisions across academic, administrative, and
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) active in the fields of materials, environment and IT. By transforming scientific knowledge into technologies, smart data and tools, LIST empowers citizens in their choices, public authorities in
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on this link to submit your application: https://academicjobsonline.org/ajo/jobs/31850 Detailed info regarding application materials required: Cover letter describing the applicant’s interest and research
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BSN Click here for more information about equivalencies: https://hr.uky.edu/employment/working-uk/equivalencies Required Related Experience No experience required. Required License/Registration
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) to streamline file management and data workflows. Support activities to prepare AI-ready multimodal datasets. AI Model Development Develop AI models for EUS segmentation Develop MRI segmentation model(s) using