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Field
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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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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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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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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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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 10 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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closely connected with quantum technologies and physical platforms. Relevant areas include but are not limited to: quantum information and computation; quantum algorithms and complexity; quantum error
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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
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, including prediabetes, type 1 and 2 diabetes, and non-alcoholic fatty liver disease (NAFLD). Their research informs artificial pancreas algorithms and contributes to drug development targeting hepatic
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the cellular and molecular pathways disrupted in brain disorders such as schizophrenia and autism, by utilizing recent advances in genetics and genomics. We are developing and applying tools to understand how