at University of Chicago in Chicago, Illinois, United States
Job Description
DepartmentPSD 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).
Application Documents
- Resume (required)
- Cover Letter (required)
- List of references (required)
When applying, the document(s) MUSTbe uploaded via the My Experience page, in the section titled Application Documents of the application.
Job Family
Research
Role Impact
Individual Contributor
FLSA Status
Exempt
Pay Frequency
Monthly
Scheduled Weekly Hours
37.5
Benefits Eligible
Yes
Drug Test Required
No
Health Screen Required
No
Motor Vehicle Record Inquiry Required
No
Posting Statement
The University of Chicago is an Affirmative Action/Equal Opportunity/Disabled/Veterans and does not discriminate on the basis of race, color, religion, sex, sexual orientation, gender, gender identity, national or ethnic origin, age, status as an individual with a disability, military or veteran status, genetic information, or other protected classes under the law. For additional information please see the University's Notice of Nondiscrimination.
Staff Job seekers in need of a reasonable accommodation to complete the application process should call 773-702-5800 or submit a request via Applicant Inquiry Form.
We seek a diverse pool of applicants who wish to join an academic community that places the highest value on rigorous inquiry and encourages a diversity of perspectives, experiences, groups of individuals, and ideas to inform and stimulate intellectual challenge, engagement, and exchange.
All offers of employment are contingent upon a background check that includes a review of conviction history. A conviction does not automatically preclude University employment. Rather, the University considers conviction information on a case-by-case basis and assesses the nature of the offense, the circumstances surrounding it, the proximity in time of the conviction, and its relevance to the position.
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