Computational Research SpecialistGeorge Mason University's Office of Research Computing invites applications for the position of Computational Research Specialist. George Mason University has a strong institutional commitment to the achievement of excellence and diversity among its faculty and staff, and strongly encourages candidates to apply who will enrich Mason's academic and culturally inclusive environment.About the Department:The Office of Research Computing supports the research cyberinfrastructure needs of the university's research and education community. Reporting to both the Vice President for Information Technology and the Vice President for Research, Innovation and Economic Impact, the office provides support for cutting-edge research technology infrastructure and activities, serving as a primary contact for research customers, coordinating the activities of research technologists and the adoption of research technologies (including software), fostering self-help communities, and maintaining a sustainable research lab support model.About the Position:The Computational Research Specialist supports the Office of Research Computing (ORC) by providing support to a diverse group of Mason researchers that need access to the ORC resources and services. The job duties include:Investigates and educates Mason researchers on the availability of both internal and external cyberinfrastructure resources;Investigates new approaches and technologies, researching and testing new solutions;Develops and maintains a comprehensive understanding of research activities across the Mason campuses;Stays current with national/international research landscape to apply appropriate technical solutions in support of the Mason researchers;Builds community on Mason campus and with national/international groups, engages in peer mentoring;Collects and reports metrics of the impact of research computing;Installs, debugs, and maintains scientific applications, and understands best use practices needed to take full advantage of the Mason's High-Performance Computing (HPC) resources;Trains and helps users adapt to a production shared resource, its scheduling system, and data storage systems;Helps produce and present tutorials/workshops in support of ORC activities;Leads or consults on data management, data processing and analytics;Provides parallel coding support and adapts serial codes;Maintains web and Wiki documentation; andOther related responsibilities include mentoring and training the GRAs and wage interns.Required Qualifications / Knowledge, Skills, and Abilities:Master's degree in computer science, computer information systems, or related field; or an equivalent combination of related experience and education;Knowledge of Linux OS;Some knowledge of Machine Learning and/or Image Analysis;Some knowledge of Message Passing Interface libraries;Some knowledge of High Performance Computing;Excellent written and verbal communication skills;Ability to write code in C, C++, Python, Java, or CUDA etc.;Some experience working with GPU and associated programming platforms (CUDA, OpenACC or OpenCL); andExperience with scripting and programming (Bash, Python, C, R).Preferred Qualifications:Ph.D. in computer science, computational sciences, and engineering or in a related field; or an equivalent combination of related experience and education;Advanced knowledge of Linux/UNIX systems;Ability to manage competing requirements in a diverse user population;Experience with distributed parallel computing architectures and software systems;Experience working with an institution wide HPC environment and associated scheduling software;Familiarity with shared memory and distributed memory parallelism (OpenMP, MPI); andExperience working with an institution wide HPC environment and associated scheduling software.Licenses/Certifications:Linux certification.
For full consideration, applicants must apply at https://jobs.gmu.edu/; complete and submit the online application; and upload a cover letter, resume, and a list of three professional references with contact information.
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