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will gain experience in a combination of field, analytical, and modeling activities. These may include: Field Research Participate in winter field campaigns to collect snowpit profiles, stability tests
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our education, while benefitting them with our talent supply and collaborative research achievements. The University’s unique applied learning pedagogy integrates work and study, embedding authentic
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assessment instruments and reporting templates into reproducible analytic products, including R-compatible templates, YAML-based table specifications, and dashboard components Learn how CDC builds capacity
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learning methods for process automation within SharePoint and Microsoft enterprise platforms. Under the guidance of a mentor, the participant will explore research approaches related to large language model
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biomarkers. Candidates should demonstrate strong organizational, analytical, and communication skills, as well as the ability to work effectively in a collaborative research environment. Prior experience with
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DNA (eDNA) metabarcoding data. This will also generate robust, accessible workflows for both short-read sequencing and long-read (e.g. Oxford Nanopore MinION) datasets. Learning Objectives: Under
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animals and animal procedures • Able to develop a research project and balance responsibility of other potential projects. • Compile data and generate computerized statistics for analytical purposes using
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 3 months ago
system and user behaviour. Join a growing portfolio of projects in artificial intelligence, natural language processing, and machine learning. These projects build on the School’s strengths in AI, machine
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data for scientific research; iii) development and application of analytical and numerical models and excellent programming skills Interest in co-supervising master and PhD students from the partner
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University of North Carolina at Charlotte | Charlotte, North Carolina | United States | about 23 hours ago
responsible for selecting appropriate methodological approaches in deep learning and optimization, formulating research problems, and determining suitable experimental and analytical strategies. Necessary