Computational Science Postdoc Fellow
The Advanced Light Source (ALS) and the Molecular Foundry (MF) at Berkeley Lab is seeking a Computational Science Postdoc Fellow to work on the development of a user friendly Machine Learning environment for scientific user facilities.
ALS is a U.S. Department of Energy Office of Science national scientific user facility whose excellent scientific reputation, expert staff, and capabilities in the soft x-ray, hard x-ray, and infrared regimes attract more than 2,000 academic and industrial users each year in disciplines spanning physical, chemical, materials, biological, energy, and Earth sciences. The Molecular Foundry is one of five national User Facilities for nanoscale science that serves over 1000 academic, industrial and government scientists around the world each year. Users come to the Foundry to perform multidisciplinary research beyond the reach of an individual’s own laboratory. The ALS and MF are two of five Berkeley Lab user facilities that serve a combined 11,000 users annually. The co-location of these user facilities – including the Molecular Foundry Nanoscale Science Research Center and the NERSC scientific computing center, as well as Berkeley Lab's outstanding programs in materials and chemical sciences among others – offers a prime environment for collaborative science. The ALS has been a global leader in soft x-ray science for more than two decades and is currently undertaking a new project (ALS-U) that will endow the facility with state-of-the-art x-ray capabilities. It's an exciting time to join our growing team!
The core values of ALS and the MF reflect a strong commitment to diversity, equity, and inclusion. We seek candidates who will support a culture in which the entire ALS and MF community feels welcomed and valued. An ongoing commitment to recruiting a vibrant, diverse and talented workforce is paramount to promoting a diverse lab community.
What You Will Do:
Develop the program for loading facility data sets and incorporate them into a multi-modal technique database.
Spearhead a focused effort to enhance data acquisition and management frameworks, query processed and analyzed data, access data from multiple instruments and facilities in a unified way, and relate these data to one another in support for multi-modal analyses.
Provide technical leadership in the area of scientific data analysis based on computing.
Work closely with ALS scientists to understand scientific questions, deploy and evaluate software to solve those specific questions.
Provide training to colleagues and write excellent documentation, to elevate the work from a proof of concept to maintainable, long-lasting infrastructure.
Develop ML models that take data from a variety of sources to promote materials discovery.
What is Required:
PhD degree in the Physical Sciences, Material Science, Applied Mathematics, Computer Science or related discipline.
Experience and a strong interest in scientific software development or research software engineering.
Experience using the open source scientific Python software stack for data analysis.
Demonstrated record of scientific excellence through publications, talks, talks, or software deliverables.
Ability to work collaboratively with a diverse team of scientists and engineers .
Experience contributing to a scientific software project in a team environment, which might include co-developing an internal project or contributing to community-based open source software.
Practical application experience of AI and ML principles and practices through industry or academic projects.
Demonstrated knowledge of core data structures, parallel programming, and designing architectures using scalable hardware and software.
Desired Qualifications:
Experience with neutron or X-ray technique, especially spectroscopy.
Contributions to open source scientific software projects.
Experience creating data analysis methods and procedures.
Demonstrated record in collaborative software development, especially in distributed teams.
Experience in data acquisition and analysis at a synchrotron light source, neutron source or other major scientific user facility.
Familiarity with widely-used AI/ML libraries such as scikit-learn, PyTorch, and TensorFlow.
Notes:
This is a full-time 3 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 2 years of paid postdoctoral experience. Salary for Postdoctoral positions depends on years of experience post-degree.
This position is represented by a union for collective bargaining purposes.
Salary will be predetermined based on postdoctoral step rates.
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 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."
Lawrence Berkeley National Laboratory encourages applications from women, minorities, veterans, and other underrepresented groups presently considering scientific research careers.