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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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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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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 15 hours 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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with Python -Experience training and evaluating machine learning models -Understanding of fundamental machine learning algorithms and best practices Course Description ARI 410 - Machine Learning CSC 375
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gene editing, and genetically distinct HBV clones to dissect the host and viral factors that determine infection and persistence. Recent work from the laboratory, published in Cell, identified a
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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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limited to, quantum algorithms and simulation, quantum error correction, open quantum systems, quantum computing, quantum communication, quantum sensing, and quantum tomography. In accordance with USCIS
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results Job Description Primary Duties & Responsibilities: Designs, develops, and implements: Algorithms and computer software for omics-based data sets [high-throughput, massively parallel genomic
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computational biologist to collaborate with a multidisciplinary team to develop innovative computational algorithms and approaches to address crucial questions in cancer biology. The role will involve
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Biologist in the Gillani Lab in Computational Pediatric Cancer Research (https://gillanilab.dana-farber.org/). The Postdoctoral Computational Biologist will work on the analysis of genomic, transcriptomic