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Field
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University of North Carolina Wilmington | Wilmington, North Carolina | United States | about 9 hours ago
scientific and technical literature; designing, adapting, and implementing computational methods, algorithms, software, simulations, prototypes, and experimental procedures to meet specific research objectives
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media trends, algorithms, platform best practices, and audience behaviors. Ability to manage multiple priorities and collaborate effectively with colleagues and partners across an organization. Experience
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. Develop algorithms to identify specific seabed characteristics. Conduct independent research related to underwater active acoustics and seabed sensing. Collaborate with researchers from academia, industry
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scalable software and algorithms for genomic inference Collaborate with researchers across statistics, genetics, and computational biology Contribute to manuscripts, presentations, and open-source software
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for probabilistic unsupervised learning for structured biological data. The successful candidate will: Develop probabilistic factor models and scalable inference algorithms for structured biological (multi-view) high
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or AI – for example, stochastic optimization and sampling algorithms, high dimensional probability, diffusion models, statistical learning theory or teaching courses on the mathematical foundations of ML
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teacher. Provides observations and assessment updates to the research team. Provides other support as needed to accomplish other related study goals. Algorithm Validation Support: Execute annotation and
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 12 days ago
include: 1. Designing and implementing software components, data structures, algorithms, APIs, and research workflows using Python and related technologies. 2. Developing and operating containerized
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applies appropriate methods to specific research problems. Proposes solutions in engineering, the sciences, and other fields using mathematical theories and techniques. Optimizes and extends algorithms
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advance pediatric, adolescent, and young adult cancer care using cutting-edge computational biology approaches. We strive to understand the germline genetics and tumor genomics of pediatric cancer to inform