Postdoctoral Scholar - Research Associate - SciTech Group

USC’s Information Sciences Institute (ISI), a unit of the university’s Viterbi School of Engineering, is a world leader in the research and development of advanced artificial intelligence, information processing, computing, cybersecurity, and communications technologies. ISI’s 400 faculty, professional staff and graduate students carry out extraordinary information sciences research at three distinct locations - Marina Del Rey, CA; Arlington, VA; and Waltham, MA.

*This position is located in Marina del Rey, CA.  Remote and hybrid work options are available.*

The USC Information Sciences Institute’s Science Automation Group (SciTech) is seeking to hire a Postdoctoral Fellow with a Ph.D. degree in computer science. This is a one-year, fixed-term appointment, with possibility of extension.

The position involves working on projects related to scientific workflow management, distributed systems, and the application of AI technologies and solutions to the management of scientific workflows in distributed environments.

The group is led by Professor Ewa Deelman, an international leader in distributed systems, high-performance systems, and scientific workflow management systems. Her group conducts research in a number of areas including resource and data management, job scheduling, provenance tracking, and the use of clouds for science. Her group has led the design and development of the Pegasus Workflow Management software, which has been adopted in a number of scientific domains and contributed to the LIGO’s first ever direct detection of gravitational waves.

The PostDoc position involves working on DOE and NSF funded projects, advancing the knowledge about distributed systems, developing novel algorithms for distributed resource and workload management, simulating and emulating systems, as well as experimentation and evaluation at scale. The position involves work in a collaborative environment working with group members as well as researchers at other universities and DOE laboratories. A successful candidate will have the desire to conduct research, learn new technologies, be able to analyze and interpret results of complex experiments on real systems and to publish these results in peer-reviewed publications. The ideal candidate will have knowledge of distributed system, data analysis methods, hands-on systems experience, and a publication record at the level of someone with a recent Ph.D. Knowledge of artificial intelligence techniques: deep learning or swarm intelligence is a plus but is not required.

The annual base salary range for this position is $85,000 - $100,000. When extending an offer of employment, the University of Southern California considers factors such as (but not limited to) the scope and responsibilities of the position, the candidate’s work experience, education/training, key skills, internal peer equity, federal, state and local laws, contractual stipulations, grant funding, as well as external market and organizational considerations.

This position is funded by a contract or grant and may be funded by a subsequent contract or grant. Accordingly, your position is contingent upon receipt of the necessary funding from this or any subsequent [contract/grant] to continue employment. In the event (a) funding for your position changes and it becomes necessary to adjust your percentage of effort; (b) or it becomes necessary for your employment with the University of Southern California to end, you will receive one (1) month written notification of termination.

According to university policy, no severance benefits are paid to employees hired under a contract or grant. When you leave, your final paycheck will include pay for days worked, and for accrued and unused vacation. The university does not pay for accrued and unused sick days upon termination.

The University of Southern California values diversity and is committed to equal opportunity in employment.

Minimum Education: Ph.D. or equivalent doctorate within previous three years Minimum Experience: 0-1 year Minimum Field of Expertise: Directly related education in research specialization with advanced knowledge of equipment, procedures and analysis methods.