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in Spatial Omics and Multi-Modal Data Integration Duties & Responsibilities: Develop computational and machine learning methods for spatial omics data (spatial transcriptomics, spatial proteomics
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of results. Highly motivated and have good communication, project management and organisational skills. Willing to learn new skills and techniques. Desirable Experience in proteomics and cancer models would be
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with course integrations Maintaining functionality of the DF virtual reality equipment Developing 3D models to provide solutions for the DF unit needs Data entry related to DF projects and processes
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this, the TUNIC project aims to develop a 3D tumour-on-chip (ToC) model incorporating primary neutrophils, tumour cells, and CD8+ T cells. This model will investigate the direct and indirect killing capacities
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cutting-edge research in areas such as pattern recognition, automation science, complex systems, AI for Science, robotics, machine learning, computer vision, natural language processing, biometrics, medical
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English and Chinese Able to work independently and in a multidisciplinary team Experience in image analysis packages such as Freesurfer, FSL, SPM, or 3DSlicer, or using machine learning or artificial
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University of North Carolina Wilmington | Wilmington, North Carolina | United States | about 18 hours ago
a full range of baccalaureate- and graduate-level programs, as well as doctoral degrees in educational leadership, marine biology, nursing practice and psychology; and many distance learning options
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, water quality and meteorological datasets routinely collected by water utilities. The student will have the opportunity of using state-of-the-art machine learning methods (predictive analytics) to analyse
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platforms and models to improve upon existing error correcting codes, while leveraging platform-specific physics knowledge, be it in ultracold neutral atoms, trapped ions or superconducting qubits. This may
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spending accounts and retirement programs. To learn more about USC benefits, access the "Working at USC" section on the Applicant Portal at https://uscjobs.sc.edu. Position Description Advertised Job Summary