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Field
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and Electronics group in the Electrification Section of EEID/ ESTD, at Oak Ridge National Laboratory (ORNL). Major Duties/Responsibilities: Develop and deploy algorithmic tools for monitoring
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that advances treatment, we educate tomorrow's physician/researchers, and we work with amazing partners, including other Harvard Medical School-affiliated hospitals. Identify suitable donor options for patients
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to develop advanced algorithms, parallel computing capabilities, and software engineering of Green’s function based multiple-scattering code for computing the electronic structure and energetics
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collection methods for external data (e.g. web scraping) to collect data for use in modelling and analysis. Develop analytic plans, engineer supporting algorithms, write new functions or applications in
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science topics, including practical software development skills. Expertise in teaching mathematical subjects related to computer science such as discrete structures, analysis of algorithms, artificial intelligence
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of Excellence for Data-Driven Discovery, applying advanced computational techniques to develop novel therapeutics. This position will work closely with researchers in the Center of Excellence for Data Driven
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software projects, including defining roadmaps, managing implementation of new features, and coordinating multiple developers. Experience working in an academic research environment, particularly quantum
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classes on embedded systems programming. Professional Development • Learn the underlying science, mathematics, statistics, data analysis, and algorithms of computational research questions. This may involve
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combination of statistical, quantitative and qualitative methods. Extracts, manipulates, and interprets data using statistical software (E.g., SPSS, R) and SQL-based query applications (e.g., Cognos) Develops
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to open-source libraries and publications in relevant journals or conferences are highly valued. Experience participating in multiple software development projects simultaneously, ensuring timely delivery