Data Management Research Scientist
·
Lawrence Berkeley National Laboratory
·
Berkeley, CA 94720
SessionJob Postings
DescriptionData Management Research Scientist - 97312
Division: DD-Data Science
Berkeley Lab’s (LBNL, https://www.lbl.gov/) Scientific Data Division has an immediate opening for a Career-Track Data Management Research Scientist to join the Scientific Data Management (SDM) Group to perform R&D on tools and technologies that bridge the performance gap between memory and storage on high performance computing (HPC) systems.
In this exciting role, you will lead to development of optimization techniques that enable storage systems to perform automatic data movement and efficient I/O operations for science applications. The developed technologies will be evaluated extensively and deployed on supercomputing systems at DOE facilities. Application programming interfaces (API) developed in this work will be available for a broader set of applications beyond science areas.
You will perform research on storage and I/O technologies for existing and future supercomputing systems. You will participate in researching and developing approaches for optimizing data access, in improving DOE applications’ data management performance on supercomputing facilities, and in helping to develop new proposals in HPC storage research as well as in the broader area of Scientific Data Management.
What You Will Do:
• Research and develop storage systems and parallel I/O technologies that affect performance of storing and accessing by scientific applications.
• Apply expertise in parallel I/O APIs and performance optimization to HPC applications.
• Research and develop object storage interface and data movement technologies for HPC, cloud, and edge computing environments.
• Document and publish work in the journals, conferences, and workshops.
• Collaborate with domain scientists and teams in making data management on HPC systems easier to use.
• Collaborate with other computer scientists, applied mathematicians, and computational scientists to ensure the resultant technologies are applicable for their respective applications and workflows.
• Interface with Principal Investigators, peers and managers at LBNL, external collaborators, sponsors, and stakeholders by conducting teleconferences, attending workshops, writing workshop reports and conference papers, and corresponding to program managers as needed.
• Contribute new ideas that can lead to research grant proposals.
• Collaborate with NERSC in evaluating storage technologies, profiling I/O, understanding I/O performance.
• May help project PI to coordinate the work of technical support staff or students.
Want to learn more about Berkeley Lab's Culture, Benefits and answers to FAQs? Please visit: https://recruiting.lbl.gov/
Notes:
• This is a full time, 2 years, career-track term appointment that may be renewed to a maximum of five years and that may be converted to career based upon satisfactory job performance, continuing availability of funds, and ongoing operational needs.
• This position may be subject to a background check. Any convictions will be evaluated to determine if they directly relate to the responsibilities and requirements of the position. Having a conviction history will not automatically disqualify an applicant from being considered for employment.
• Work may be performed on-site or hybrid. The primary location for this role is Lawrence Berkeley National Lab, 1 Cyclotron Road, Berkeley, CA. Work must be performed within the United States.
How To Apply
Apply directly online at http://50.73.55.13/counter.php?id=244053 and follow the on-line instructions to complete the application process.
Based on University of California Policy - SARS-CoV-2 (COVID-19) Vaccination Program and U.S Federal Government requirements, Berkeley Lab requires that all members of our community obtain the COVID-19 vaccine as soon as they are eligible. As a condition of employment at Berkeley Lab, all Covered Individuals must Participate in the COVID-19 Vaccination Program by providing proof of Full Vaccination or submitting a request for Exception or Deferral. Visit covid.lbl.gov (https://covid.lbl.gov/) for more information.
Berkeley Lab is committed to Inclusion, Diversity, Equity and Accountability (IDEA, https://diversity.lbl.gov/ideaberkeleylab/) and strives to continue building community with these shared values and commitments. Berkeley Lab is an Equal Opportunity and Affirmative Action Employer. We heartily welcome applications from women, minorities, veterans, and all who would contribute to the Lab’s mission of leading scientific discovery, inclusion, and professionalism. In support of our diverse global community, all qualified applicants will be considered for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, or protected veteran status.
Equal Opportunity and IDEA Information Links:
Know your rights, click here (https://www.dol.gov/agencies/ofccp/posters) for the supplement: Equal Employment Opportunity is the Law and the Pay Transparency Nondiscrimination Provision (https://www.dol.gov/sites/dolgov/files/ofccp/pdf/pay-transp_%20English_formattedESQA508c.pdf) under 41 CFR 60-1.4.
Division: DD-Data Science
Berkeley Lab’s (LBNL, https://www.lbl.gov/) Scientific Data Division has an immediate opening for a Career-Track Data Management Research Scientist to join the Scientific Data Management (SDM) Group to perform R&D on tools and technologies that bridge the performance gap between memory and storage on high performance computing (HPC) systems.
In this exciting role, you will lead to development of optimization techniques that enable storage systems to perform automatic data movement and efficient I/O operations for science applications. The developed technologies will be evaluated extensively and deployed on supercomputing systems at DOE facilities. Application programming interfaces (API) developed in this work will be available for a broader set of applications beyond science areas.
You will perform research on storage and I/O technologies for existing and future supercomputing systems. You will participate in researching and developing approaches for optimizing data access, in improving DOE applications’ data management performance on supercomputing facilities, and in helping to develop new proposals in HPC storage research as well as in the broader area of Scientific Data Management.
What You Will Do:
• Research and develop storage systems and parallel I/O technologies that affect performance of storing and accessing by scientific applications.
• Apply expertise in parallel I/O APIs and performance optimization to HPC applications.
• Research and develop object storage interface and data movement technologies for HPC, cloud, and edge computing environments.
• Document and publish work in the journals, conferences, and workshops.
• Collaborate with domain scientists and teams in making data management on HPC systems easier to use.
• Collaborate with other computer scientists, applied mathematicians, and computational scientists to ensure the resultant technologies are applicable for their respective applications and workflows.
• Interface with Principal Investigators, peers and managers at LBNL, external collaborators, sponsors, and stakeholders by conducting teleconferences, attending workshops, writing workshop reports and conference papers, and corresponding to program managers as needed.
• Contribute new ideas that can lead to research grant proposals.
• Collaborate with NERSC in evaluating storage technologies, profiling I/O, understanding I/O performance.
• May help project PI to coordinate the work of technical support staff or students.
Want to learn more about Berkeley Lab's Culture, Benefits and answers to FAQs? Please visit: https://recruiting.lbl.gov/
Notes:
• This is a full time, 2 years, career-track term appointment that may be renewed to a maximum of five years and that may be converted to career based upon satisfactory job performance, continuing availability of funds, and ongoing operational needs.
• This position may be subject to a background check. Any convictions will be evaluated to determine if they directly relate to the responsibilities and requirements of the position. Having a conviction history will not automatically disqualify an applicant from being considered for employment.
• Work may be performed on-site or hybrid. The primary location for this role is Lawrence Berkeley National Lab, 1 Cyclotron Road, Berkeley, CA. Work must be performed within the United States.
How To Apply
Apply directly online at http://50.73.55.13/counter.php?id=244053 and follow the on-line instructions to complete the application process.
Based on University of California Policy - SARS-CoV-2 (COVID-19) Vaccination Program and U.S Federal Government requirements, Berkeley Lab requires that all members of our community obtain the COVID-19 vaccine as soon as they are eligible. As a condition of employment at Berkeley Lab, all Covered Individuals must Participate in the COVID-19 Vaccination Program by providing proof of Full Vaccination or submitting a request for Exception or Deferral. Visit covid.lbl.gov (https://covid.lbl.gov/) for more information.
Berkeley Lab is committed to Inclusion, Diversity, Equity and Accountability (IDEA, https://diversity.lbl.gov/ideaberkeleylab/) and strives to continue building community with these shared values and commitments. Berkeley Lab is an Equal Opportunity and Affirmative Action Employer. We heartily welcome applications from women, minorities, veterans, and all who would contribute to the Lab’s mission of leading scientific discovery, inclusion, and professionalism. In support of our diverse global community, all qualified applicants will be considered for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, or protected veteran status.
Equal Opportunity and IDEA Information Links:
Know your rights, click here (https://www.dol.gov/agencies/ofccp/posters) for the supplement: Equal Employment Opportunity is the Law and the Pay Transparency Nondiscrimination Provision (https://www.dol.gov/sites/dolgov/files/ofccp/pdf/pay-transp_%20English_formattedESQA508c.pdf) under 41 CFR 60-1.4.
RequirementsWhat is Required:
• PhD degree in applied mathematics, computer science, physics, or related fields or equivalent combination of education and experience.
• Demonstrated expertise in the optimizing storage systems and I/O libraries.
• Demonstrated experience in working with high-performance computing applications using C/C++, Python, R, MPI, and I/O libraries, such as HDF5 and MPI-IO.
• Demonstrated experience in performance modeling and performance analysis for parallel I/O.
• Demonstrated experience in using distributed-memory computing platforms.
• Proficient with C/C++, MPI.
• Extensive working knowledge of common I/O libraries including HDF5, netCDF, and MPI-IO.
Desired Qualifications:
• Familiar with the internals of I/O libraries such as HDF5.
• Familiarity with HPC I/O performance software stack and optimizations.
·
·
2022-11-14
Event Type
Job Posting
TimeWednesday, 16 November 202210am - 3pm CST
Location