Position: HPC Application Specialist (9099)
Working as a senior member of a team, carries out complex or leading-edge scientific and technical efforts related to research projects. Frequently acts as team leader, in particular with problem formulation and procedural determinations for unique and unusual situations. Work has significant impact on project outcomes. The HPC Applications Specialist will join the Pittsburgh Supercomputing Center’s Strategic Applications Group, which addresses hardware and software architectures for scalable, high-performance, and data-intensive computing, data analytics including visualization, future technologies, facilitating cutting-edge research on emerging computer systems, and enabling novel applications. Tasks for the HPC Applications Specialist will include a combination of some or all of the following: performance analysis and modeling of algorithms, applications, and hardware architectures; working with researchers and applications to enable efficient, transformative use of PSC and XSEDE resources; development and optimization of applications and libraries for emerging technologies (e.g. GPGPUs); supporting data-intensive programming models, workflows, and technologies; supporting projects using high-productivity programming models (e.g. Python); and attracting external funding.
Education: Master's degree in a computational science discipline, computer science, or applied math, or equivalent combination of training and experience.
Experience: Four or more years experience in a computational science discipline, computer science, or applied math. Four or more years demonstrated success in parallel computer systems to the solution of research problems in computational science or engineering.
Skills: Strong knowledge of analysis of algorithms. Strong scientific programming skills using C, C++, Java, CUDA, Fortran, MPI, and/or OpenMP. Broad understanding of the design and architecture of contemporary high performance computing systems: CPUs, accelerators, chipsets, shared and distributed memory architectures, interconnection networks, storage systems, and related system software. Familiarity with contemporary approaches to measurement and analysis of the performance of such computing systems and of the scientific codes that run on them. Good technical writing, documentation, and public presentation skills. Ability to give public presentations and to interact and communicate very well with other people. Ability to apply mastery and broad understanding in a specific field (i.e., computer science, chemistry, electrical engineering, design, etc.) to practical scientific or technical projects; excellent analytical, technical, reasoning and innovative problem solving skills; ability to function competently in a team environment; ability to interact and communicate effectively and courteously with members of the campus community and external customers; ability to maintain accurate and detailed records.
Physical Mobility: Normally sedentary with some mobility; i.e., able to travel to other campus locations. Some travel will be required.
Environmental Conditions: Work is normally performed in PSC's offices (Pittsburgh, Pennsylvania). There is frequent close contact with CRT for long periods of time.
Mental: Ability to pay close attention to detail, meet inflexible deadlines, remain calm during difficult situations, work under pressure and work with frequent interruptions, supervise others.
Other: Week-end and evening hours may be required.
Education: Doctorate in a computational science discipline, computer science, or applied math, or equivalent combination of training and experience.
Experience: Peer-recognized expertise in HPC or data-intensive software development, machine learning, data analytics, accelerator programming, algorithm analysis or development, HPC systems performance research; attested substantial personal contributions to publications, awards, and grants for research in these fields.
Skills: Familiarity with major applications, libraries, and workflows in one or more scientific application areas. Detailed understanding of the design and architecture of contemporary HPC and/or data-intensive systems: CPUs, accelerators, chipsets, shared and distributed memory architectures, interconnection networks, storage systems, and related system software. Expertise in performance measurement and modeling. Expertise in one or more of the following: technologies for data-intensive computational science, accelerator programming, Java, and/or machine learning. Demonstrated ability to plan and execute individual and collaborative research.
Mental: Ability to propose, be funded for, and execute original research.
To apply submit your credentials online at http://www.cmu.edu/jobs/index.html. No applications will be accepted via email or snail mail.
Carnegie Mellon University is an Affirmative Action/Equal Opportunity employer.