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://www.academictransfer.com/en/jobs/357341/postdoc-position-on-federatedco… Requirements Specific Requirements We are looking for a researcher who sits at the intersection of Pervasive/Mobile Computing and Machine Learning
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undergraduates in scientific research projects. ESSENTIAL DUTIES & RESPONSIBILITIES INCLUDE: 1) Computer simulations of protein structure and computational protein design of small peptides and proteins. 2
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Responsibilities Salary Range: $80,000 – $100,000 Benefits Information: https://www.luc.edu/hr/benefits/ We are seeking a highly motivated data scientist to join our group, which has been supported by federal funds
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experience in Artificial Intelligence (AI) and Machine Learning (ML) concepts, algorithms, and frameworks; Hands-on experience with popular ML libraries and tools (e.g., TensorFlow, PyTorch, scikit-learn
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use of laboratory equipment, including vibratome, scales, stirrers, pH meter, and knows or will learn any and all equipment, software, and specialized materials needed to support the effective and
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 5 days ago
efforts with other laboratories will be promoted to allow the RA to learn new techniques. Education and Experience: Complete several different tasks simultaneously and have excellent time management skills
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PhD Research Fellow in ML-assisted reservoir characterization/modelling for CO2 storage (ref 290702)
-build ups in potential multi-site storage licenses. The research will help to suggest best practices for machine learning integration in de-risking CO2 storage sites. We seek a candidate with a strong
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machine learning with single-cell genomics, spatial omics, and systems biology, supported by strong collaborations across UBC and internationally. Project Recent advances in single-cell and spatial omics
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combination of remote sensing, machine learning, historical map analysis, records-based research and selective archaeological surveys. It is working to make records of these sites openly available in an Arches
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, using a combination of remote sensing, machine learning, historical map analysis, records-based research and selective archaeological surveys. It is working to make records of these sites openly available