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Field
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maintenance of machine learning algorithms, applications, analysis pipelines, and results reporting methodologies using R and SAS (including R functions and SAS macros for data management and analysis support
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analysis of nuclear cardiology data using novel algorithms and machine learning techniques, and on the development of integrated motion-corrected analysis of positron emission tomography (PET)/computed
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peer-reviewed journals. The Research Scientist works with large-scale datasets, conducts experiments to validate hypotheses, and refines algorithms for efficiency, scalability, and interpretability
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of interventions. (70%) Responsible for the development, implementation, and ongoing management of one or more ongoing clinical programs, including but not limited to: evidence-based clinical algorithms
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ranging from introductory to more advanced topics such as: Introduction to Computer Science and Software Development Object Oriented Programming and Problem Solving Algorithms and Data Structures
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emissions and soil health parameters. Results will be published in peer-reviewed journals and technical reports, and algorithms and models will be shared with stakeholders and the scientific and forest
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manner. Collaborative Innovation: Lead and participate in collaborative initiatives aimed at developing novel computational tools, algorithms, and models that address critical challenges in drug discovery
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emissions and soil health parameters. Results will be published in peer-reviewed journals and technical reports, and algorithms and models will be shared with stakeholders and the scientific and forest
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these transcripts into protein sequence databases. Guide the development of proteogenomics through implementation of novel algorithms and computational analysis infrastructure Development of tools to support clinical
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Responsibilities* Experimental responsibilities will include, but not be limited to: Develop and implement advanced AI/ML algorithms for image segmentation and registration Collaborate with diverse teams in