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foundation models. ? Expertise with developing efficient data loaders for large datasets and optimizing training workflows. ? Deep knowledge of probabilistic modelling, self-supervised learning and
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experience analyzing and linking large datasets. Good understanding of the types of public domain data that are used in public health analyses and have experience utilizing these datasets. Demonstrated
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to develop and test alternative approaches to existing tools. Manage and curate large datasets, ensuring data integrity and accessibility. Develop and maintain databases to organize and query genomic and
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. Work experience may NOT substitute for education requirement. Preferences Ability to act independently Ability to analyze and interpret data Ability to assimilate, trend, and present data to large groups
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for applicants. Manages communication with large volumes of applicants through various stages of follow-up. Provides admissions process information to prospective students and provides applicants with admissions
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research facilities for small and large animals, including a gnotobiotic facility and BORC's animal imaging facility, nanoparticle tracking analysis, microscopy facilities, metabolic cages, phenotyping, and
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coordination of large amounts of data with individuals in research labs, and the maintenance of records and generation of reports and scientific writing needs (e.g., journal articles, white papers, etc
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using large-scale state administrative panel data and survey data collected from students, teachers, and principals across the state of Michigan in both descriptive and quasi-experimental econometric
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, disability, age, genetic information, veteran status, marital status, and/or political affiliation. See https://equity.unl.edu/notice-nondiscrimination/ Minimum Required Qualifications: Bachelor's degree in
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fluid dynamics. The successful candidate will be expected to work on all or a subset of the above topics, be proficient in working with large data-sets (observational or numerical), machine learning, and