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or experience in nontraditional research publication methods and collaborative notetaking software (e.g., Roam Research, Obsidian, Notion). ? Familiarity with cloud computing and machine learning techniques
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evidencing: which scientific discoveries are more impactful than others; whether public attitudes to science change over time; how the public learn and talk about science; how different target groups respond
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of remedial rules and institutions. Reframing remedies as an intermediary link between different systems crucial in the production of our imaginaries of justice, CURE aims to provide a new reading of labour law
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University of North Carolina Wilmington | Wilmington, North Carolina | United States | about 3 hours ago
access helps us provide an enriching learning environment for students, faculty and staff interested in the marine sciences. College Center for Marine Science - 306 College College/School Information
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results. Machine Learning skills to automise comparison process. Unbiased approach to different theoretical models. Experience in HPC system usage and parallel/distributed computing. Knowledge in GPU-based
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AgriLife is uniquely positioned to improve lives, environments and the Texas economy through education, research, extension and service. Click here to learn more about how you can be a part of AgriLife and
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Scholar appointments to a total of five years, including postdoctoral experience(s) at other institutions. The University of Washington and the International Union, Automobile, Aerospace and Agricultural
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in Dr. Shanlin Ke’s lab. The overarching goal of Dr. Ke’s lab is to develop computational approaches and leveraging bioinformatics tools, metagenomic sequencing, multi-omics data, machine learning, and
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the Interpretable Machine Learning Lab (https://users.cs.duke.edu/~cynthia/home.html ) for a scientific developer to work in collaboration with other researchers on machine learning tools that help humans make better
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experience in the analysis of metagenomics and/or biological high-throughput data Knowledge of statistical and machine learning methods in the context of biological systems Experience with programming (e.g