Berkeley Lab (LBNL) addresses the world’s most urgent scientific challenges by advancing sustainable energy, protecting human health, creating new materials, and revealing the origin and fate of the universe. Founded in 1931, Berkeley Lab’s scientific expertise has been recognized with 13 Nobel prizes. The University of California manages Berkeley Lab for the U.S. Department of Energy’s Office of Science.
Position Summary:
Berkeley Lab’s NERSC Division has an opening for an Exascale Science Applications Postdoctoral Fellow for Data (NESAP). We are looking for highly motivated postdocs to join the NERSC ExaScale Application Readiness Program (NESAP), funded by the US Department of Energy Office of Science. These postdocs will participate in “NESAP for Data,” collaborating with scientific teams to enable the solution of deep, meaningful problems in data-intensive experimental/observational sciences like cosmology, high-energy physics, neuroscience, and imaging.
The Challenge: To enable advanced data science and knowledge discovery at scale on energy-efficient supercomputers. In search of answers to some of the deepest questions of our time, scientists pursue ever-increasing volumes of data, and seek to explore data with computationally intensive algorithms. To meet these demands, NERSC has deployed Cori, a 30 petaflop Cray XC40 supercomputer (named in honor of Gerty Cori, the first American woman to win a Nobel Prize in science). Cori was designed for large-scale simulations, modeling, and data analysis. It is based in part on the new energy-efficient Intel Xeon Phi/Knights Landing (KNL) many-core processor. Cori includes a number of features especially friendly to data-intensive science users. For instance, it is the first high-performance computing (HPC) resource to incorporate a Burst Buffer, a layer of non-volatile storage, especially useful for big data workloads from scientific experiments.
NESAP for Data explicitly addresses data-intensive science applications that rely on processing and analysis of massive datasets acquired from experimental and observational sources. These sources may include spectrographs like the Dark Energy Spectroscopic Instrument, telescopes studying the cosmic microwave background, genome sequencers at the Joint Genome Institute, synchrotron sources like the Advanced Light Source, or particle detectors at the Large Hadron Collider. The objective of this program is to enable applications processing data from such sources to take full advantage of the KNL chipset on Cori.
Many current algorithms for data analysis used in experimental science contexts are not optimized for many-core architectures. Some are written in “productivity” languages like Python, not “performance” languages like C, C++ or Fortran. In this project, we will employ the latest advances in computer science to develop highly scalable, distributed parallel algorithms to overcome these challenges.
Fellows will be working in multidisciplinary teams composed of computer, computational, and domain scientists that will transition codes to the Cori system and produce mission-relevant science that truly pushes the limits of high-end computing. You will carry out code transition efforts in collaboration with project PI and team members and with the support of NERSC and vendor staff.
What You Will Do:
Work with NERSC staff and code teams to transition and optimize data-intensive science codes to the KNL architecture; conduct profiling and scaling studies as well as vectorization and memory bandwidth analyses for these codes; address issues specific to experimental analysis codes within the big data ecosystem at NERSC.
Disseminate results of research activities through refereed publications and conference presentations. Ensure that new methods are suitably documented for the wider experimental science community, NERSC staff, vendors, and other NERSC users.
May involve travel to sites at other labs and universities.
Participation in postdoctoral career and science enrichment activities within the Berkeley Lab Computing Sciences Area will also be encouraged.
What is Required:
Ph.D. in Computer Science, Computational Science, Applied Mathematics, or a science domain area with a computationally-oriented research focus.
Research experience and knowledge in computing and/or code development ideally for experimental science or HPC.
Demonstrated communication and interpersonal skills.
Experience in applied mathematics, algorithm design, or scientific computing.
Ability to work productively both independently and as part of an interdisciplinary team balancing divergent objectives involving research and code development.
Additional Desired Qualifications:
Experience with the development and performance optimization of scientific software in an HPC context.
Experience with many-core and parallel computer architectures, threading and vectorization.
Experience in the development and application of modern distributed parallel computing environments such as Spark, and experience with modern high-level programming languages like Python, Julia, or Java.
Contributions in the form of publications or collaboration on open source software projects.
The posting shall remain open until the position is filled.
When Applying:
Please do include a cover letter introducing yourself and your application.
Either a Curriculum Vitae or Resume are acceptable.
In your cover letter or CV/Resume please do call out any and all technical skills you have that are relevant to this position.
A list of publications is encouraged.
Provide contact information for three references whom we can contact regarding your application.
Notes:
This is a full time 1 year postdoctoral appointment with the possibility of renewal based upon satisfactory job performance, continuing availability of funds and ongoing operational needs. You must have less than 3 years paid postdoctoral experience. Salary for Postdoctoral positions depends on years of experience post-degree.
Full-time, M-F, exempt (monthly paid) from overtime pay.
This position is represented by a union for collective bargaining purposes.
Salary will be predetermined based on postdoctoral step rates.
Work will be primarily performed at Lawrence Berkeley National Lab, 1 Cyclotron Road, Berkeley, CA.
Equal Employment Opportunity: Berkeley Lab is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, or protected veteran status. Berkeley Lab is in compliance with the Pay Transparency Nondiscrimination Provision under 41 CFR 60-1.4. Click here to view the poster and supplement: "Equal Employment Opportunity is the Law."
