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Proficiency in Python AI/ML libraries (PyTorch, scikit-learn, OpenCV) Experience with natural language processing, computer vision, statistical modeling, or other machine learning algorithms Experience with CI
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University of California San Francisco | San Francisco, California | United States | about 2 months ago
cardiovascular diseases. More specifically, the role involves developing and utilizing computational tools and systems to analyze and interpret biological or other research data. Utilizes and develops algorithms
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. The Sheltzer Laboratory is broadly interested in identifying the genetic changes that occur during tumorigenesis and influence drug sensitivity, metastasis, and patient outcomes. We apply a number of high
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. The Senior Bioinformatics Analyst works with research staff to extend capabilities in bioinformatics and improve understanding of genetic variation in human health and disease. The Senior Bioinformatics
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Primary Work Address: Dept. of Genetics, Boston, MA, 02115 Current HHMI Employees, click here to apply via your Workday account. We are currently seeking a dynamic, interested, and curious Research
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and augmented reality, e-commerce, image and video processing, scientific and interactive visualization, high-performance computing, scalable algorithms, bioinformatics, and multi-scale multi-physics
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Internal Number: JR93463 Scheduled Hours 40 Position Summary Assists in application development and integration on our High-Performance Computing (HPC) cluster used by researchers across disciplines. Work
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statistics, AI, and computation to generate biological and medical insight. The group focuses on the development of novel algorithms, tools, and databases that are open source and freely available to all users
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One‑year term position Be You. The Duke Center for Computational Thinking (CCT) is looking for a Web Developer to join our collaborative team advancing computational literacy across Duke University
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the construction of PRS and enhance disease prediction. Students will gain experience in: Statistical genetics and GWAS methodology Machine learning approaches for high-dimensional data Algorithm development and