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PSD Computer Science: Administration and Staff

About the Department

The Department of Computer Science (CS) is a research leader in computer systems. CS is part of the Physical Scienced Division. CS well-known for leading research in future computer systems. The UpDown Computer project includes well-known researchers in computer architecture, operating systems, machine learning, and graph algorithms.

Job Summary

The Senior Research Specialist (SRS) will work as an important research staff member on the UpDown Computer research project. The UpDown computer is an ambitious novel computer design that seeks to increase performance on graph applications by over 100-fold, and scale up to 25,000 nodes. As such, the UpDown computer would achieve graph analytic abilities far in excess of the capabilities of the world\'s fastest supercomputer and cloud systems.

The Senior Research Specialist (SRS) will work with a diverse team of six PI\'s whose expertise ranges from computer architecture, hardware design, operating systems, and graph algorithms. The overall team of over 15 members also includes four postdocs and five graduate students. The SRS will play a key role in project success, contributing individually to hardware design, simulation, and software to evaluate the UpDown architecture. As needed the SRS will help organize and drive development and integration/test to deliver internal and external milestones. The SRS will contribute to research design and simulation of the UpDown computer, including research publications and reporting to funding agencies. Position will report to project PI (Chien), who is an experienced computer architecture researcher and industry executive.

Responsibilities

• As a team leader, works collaboratively with colleagues to define architecture specifications, simulate, evaluate, and realize in hardware.
• Leads the team on the creation of architecture models (software and in HDL) to enable evaluation for performance and hardware implementation metrics such as size, power, speed.
• Works with team, driving software and hardware integration, to enable large complex system modeling and research evaluation.
• Develop and cultivate ongoing relationships with the team for an effective large-scale system and graph application simulation.
• Manages the software infrastructure project - git, software and hardware development tools -- to enable project team research to succeed.
• Contributes to reporting - data, graphics, slides, presentation, reports - for the funding organization.
• Leads the cloud software infrastructure project - AWS, EC2 - and hardware simulation - FireSIM, SST, to enable project team research to succeed.
• Facilitates collaborations across the teams in the UpDown Computer project.
• Provides expertise to researchers and research support staff. Oversees activities related to data collection and analysis.
• Improves financial, personnel, planning, compliance and other administrative aspects of research project. Collaborates with other researchers on long-range plans for research projects. Leads, investigates, modifies and applies new procedures, techniques or applications of technology. Establishes goals and operating procedures, practices, and guidelines.
• Trains and mentors graduate students and postdoc personnel.
• Performs other related work as needed.

Minimum Qualifications

Education:

Minimum requirements include a college or university degree in related field.

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Work Experience:

Minimum requirements include knowledge and skills developed through 7+ years of work experience in a related job discipline.

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Certifications:

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Preferred Qualifications

Education:

• MS in Computer Science, Computer Engineering, Electrical Engineering, or related field.

Experience:

• Large complex software and/or hardware systems.
• Computer architecture or systems design, implementation, and evaluation.
• Computer architecture research, Systems software research.
• Experience in Performance programming.

Technical Skills or Knowledge:

• Software tools such as git, llvm, testing.
• Hardware tools such as Verilog/vhdl, synopsys/cadence, OpenRoad.
• Graph algorithms and analytics.
• Parallel computation.
• Systems performance analysis.

Preferred Competencies

Knowledge of complex software design, implementation, test, version control, and documentation.

Knowledge of complex hardware design, implementation, test, version control, and documentation.

Experience in Parallel Computing; Cloud application development (using AWS and EC2).