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Field
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background in computational biology, modeling or Machine Learning and Artificial Intelligence Familiarity with basic techniques and principles in cell and molecular biology and biochemistry Willing to learn
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Oncology Department at City of Hope is the largest Radiation Oncology enterprise in the southern California with more than 25 Linear Accelerators (Linacs) including special designed machines such as MR
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operations, such as data storage, budgets, expenses, assets, and ethics approvals. Key Responsibilities: Conduct independent and collaborative research applying AI and machine learning techniques
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development of transparent, closed-loop control system for individualized diuretic closing including the validation and advancement of machine-learning and control algorithms, building production-oriented
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. graduates and doctoral candidates nearing graduation who have research interests in applied statistics, machine learning, or computational biology to apply for our postdoctoral fellows program. Located in
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design and discovery, including the use of artificial intelligence (AI) and machine learning (ML) techniques. The hired candidate will focus on computational aspects of immune repertoire analyses
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, automated reasoning and symbolic AI, and machine learning and neural AI. Applicants should submit their cover letter, research statement, CV, and list of references to positions@icarm.io. Applications will be
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a PhD in machine learning, math, stats, physics, or some other technical area by the time the position starts. Additional Qualifications Candidates should have significant experience in some area of
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part of the Structural Genomics Consortium (SGC) Target 2035 Initiative, a global collaboration in the area of protein science, machine learning and data science towards improving our ability to predict
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computational pipelines for multiplex imaging, spatial transcriptomics, single cell RNAseq, and multi-omics data integration. Lead graph-based network and machine learning analyses of tumor immune