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Field
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to contribute to a comprehensive understanding of the germline genetics and tumor genomics of pediatric cancer to inform novel approaches to the management of pediatric cancer. We value great science that matters
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ensuring that the data are of high quality and running algorithms to identify genomic alterations. The goal of this research is to result in a published manuscript. Basic Qualifications BS in computational
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, develop, and evaluate predictive models and algorithms that lead to optimal value extraction from the data. Evaluates and implements novel approaches to address aims and milestones to multilayered datasets
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help develop new computational models that integrate molecular reaction networks with AI/ML algorithms in order to predict patient-specific cardiac remodeling and heart disease outcomes across human
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that integrate rodent pain models, mouse genetics, circuit-level approaches, molecular and cellular assays, high-resolution imaging, behavioral phenotyping, and quantitative data analysis. This role will also
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3 – Quantum algorithms for data clustering: Clustering algorithms are of fundamental importance when dealing with large unstructured datasets and discovering new patterns and correlations therein
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Primary Duties & Responsibilities: Implements: Algorithms and computer software for analyzing omics-based data sets [high-throughput, massively parallel genomic/proteomic/clinical]; Data management and
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. Responsibilities: Conduct research on automated reasoning and proof checker, AI-assisted collaboration. Develop and analyze algorithms for learning and optimization. Participate in collaborative research projects
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and efficiency of life sciences research. Developing the algorithms, infrastructure, and governance necessary for such analysis can simultaneously enhance hypothesis generation, computational modeling
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fields, develops the algorithms that power the information age, and is committed to creatively and thoughtfully exploring technology's potential to advance our world. Cornell Bowers is home to more than