Data Science & Technology – Postdoctoral Researcher
Lawrence Berkeley National Laboratory
Be a part of addressing the next generation of science research problems. There is an immediate opening for a postdoctoral researcher to work on a collaborative project at the interface of biology and computing. The Postdoc will work collaboratively with the Data Science and Technology (DST) department in the Computational Research Division and Joint Genome Institute (JGI) at Lawrence Berkeley National Laboratory (LBNL). The postdoctoral researcher will perform cutting edge research and development in software systems, with the goal of enabling and supporting the JGI scientific community to better understand methane flux in the amazon , engineer better biofuels , explore viral diversity , and more.
We are looking for a postdoctoral researcher with a demonstrated track record of strong research, programming, and data analysis skills interested in working to help create the next generation of methods, algorithms and tools for scientific data on large-scale computing systems.
The Data Science and Technology department develops software and tools to enable scientists to address complex and large-scale computing and data analysis problems beyond what is possible today. DST engages in partnerships with scientists to understand their computing and data analysis challenges to develop leading-edge solutions that fit the needs of the scientists. Current research areas and projects include workflow tools, user-level abstractions for exascale data discovery, development of new techniques to secure high- performance computing and networking environments, computationally-driven discovery of new materials, and processing pipelines for scientific data. More details on projects available on https:// dst.lbl.gov/projects.
The JGI is a Department of Energy (DOE) national user facility with origins in the Human Genome Project that supports thousands of scientists in the generation and analysis of multi-omic data. The Data Science and Informatics Department at the JGI develops software and tools to remove barriers to data access and analysis for the scientific community. JGI is comprised of highly- skilled and diverse talent founded on a culture of scientific excellence, trust, curiosity, passion, and collaboration.
Working at Berkeley Lab has many rewards including a competitive compensation program, excellent health and welfare programs, paternal leave, a retirement program that is second to none, and outstanding employee development opportunities. To view information about the many rewards that are offered at Berkeley Lab- Click Here.
What you will do:
Write scientific research papers suitable for submission to peer-reviewed computer science venues, in research areas connected to high-performance computing and networking, secure cyberinfrastructure, and scalable data discovery.
Assist in writing proposals to obtain sponsored research funding.
Enable usable and scalable large-data discovery through applications of machine learning on distributed cyber-infrastructure.
For all of the above, work closely with researchers and application scientists throughout the Department of Energy (DOE) Office of Science and DOE Applied Energy Office community. This position will also work closely with faculty and students from universities throughout the world, with industry partners, with staff in Integrated Data Frameworks group at LBNL, where this position is housed; the Energy Sciences Network (ESnet); the NERSC production computing facility; and other DOE Leadership Computing Facilities.
PhD degree in computer science, computer engineering, bioinformatics, or a related technical field.
Experience with fundamentals of computer systems or machine learning.
Proven experience writing software and proficiency and experience in programming languages such as C/C++ and/or Python.
Proficiency with UNIX tools and computer systems.
Demonstrated ability to work independently and collaboratively in a diverse interdisciplinary team and contribute to an active intellectual environment.
Established record of peer reviewed publications
Experience with key tools used in scientific data discovery, such as Jupyter notebooks, Spark, and/or related software systems.
Experience with data movement and manipulation; leveraging workflow tools; and using APIs for interacting with libraries and databases.
Experience with working in large scientific collaborations or bioinformatics datasets.
Experience with computational methods used in scientific computing, and high-performance computing environments, including parallel languages and execution environments.
The posting shall remain open until the position is filled.