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Field
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and efficiency of life sciences research. Developing the algorithms, infrastructure, and governance necessary for such analysis can simultaneously enhance hypothesis generation, computational modeling
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quantum chemical methods and machine learning; developing quantum algorithms for computational chemistry on quantum computers; and applying existing and new computational methods to study multiscale
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three years The candidate will hold primary responsibility for designing novel algorithmic frameworks, coordinating multi-institutional research networks, and translating real-world health data
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quantitative modeling techniques and artificial intelligence methodologies in brain diseases. The candidate will work on developing advanced new algorithms, testing and validation, and applications in these data
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graph-based algorithms for genetic data. The specific project involves understanding the unique evolutionary histories of diverse populations, both in humans and other species. The research specialist
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will include development of algorithms for heterogeneous computing architectures and implementation of AI/ML in a real-time environment. The candidate will also have the opportunity to conduct
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 months ago
Health, powered by the All of Us Research Program is a new initiative to develop algorithms that predict individual responses to food and dietary patterns. The NPH Consortium consists of 12 awardees across
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Department's Website: https://engineering.uark.edu/ Summary of Job Duties: Collaborating closely with Dr. Richardson and students in our group, the Postdoctoral Research Associate - Chemical Engineering will
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improvement of the Ellucian Banner Financial Aid module, including rules tables, packaging algorithms, need analysis parameters, fund management, and award letter automation. Manage the financial aid components
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Primary Duties & Responsibilities: Implements: Algorithms and computer software for analyzing omics-based data sets [high-throughput, massively parallel genomic/proteomic/clinical]; Data management and