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California State University, San Bernardino | San Bernardino, California | United States | about 23 hours ago
. Key Responsibilities: Peer Educator & Role Model: As an Orientation Leader, you will serve as a peer educator and role model, setting a positive example for incoming students. Responsibilities: Under
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transitions in and out of campus housing, accurate data reporting, and collaborative partnerships across departments. As part of our integrated residential education model, you’ll work closely with professional
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to analyze data and experience with statistical, machine learning, and data science approaches. Prior experience working in teams on collaborative projects. Knowledge, Skills and Abilities: Expertise in one
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predictive modelling; Bioinformatics and Knowledge Graphs (visualization and reporting); AI-based data integration across cohorts (with federated machine learning); Contribute to ongoing projects, such as: o
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computational analyses of single-cell, spatial transcriptomics, and multi-omics datasets Developing and maintaining reproducible, well-documented analysis pipelines Applying and adapting machine learning and AI
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of scientific computing involving machine learning models for viscoelastic fluid flows. Legislation and regulations: Law Nº. 40/2004, of 18th August, in its current wording (Statutes of Scientific Research Fellow
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efficiency. Experience working with R or Python data science tools to analyze and visualize health care data and to develop data pipelines to support machine learning model development. Experience working with
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is seeking an Infrastructure Architect Senior to design and operate the platform infrastructure that supports Michigan Online and CAI's digital learning ecosystem. Reporting to the Director of
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models with drone imagery using machine learning techniques and data assimilation. The work will involve collaboration with an interdisciplinary team of researchers, engineers, and local stakeholders in a
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of an artificial intelligence (AI) solution for the diagnosis of invasive fungal infections, using microscopy images obtained in laboratory settings with limited resources. Leveraging deep learning models such as