Berkeley Lab - California - The Advanced Light Source Division at Berkeley Lab is seeking a Computational Science Postdoc Fellow Postdoc from the Theoretical and Computational Sciences to work on accelerating materials discovery using Artificial Intelligence and Machine Learning techniques (AI/ML). The 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. It is one 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 the Advanced Light Source (ALS) reflect a strong commitment to diversity, equity, and inclusion. We seek candidates who will support a culture in which the entire ALS 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: The postdoc will lead the design, development, and optimizations of a platform for AI/ML-guided materials discovery, using spectroscopic data sets available at DOE user facilities. The postdoc will report to the project leads, Dylan McReynolds and Wanli Yang. Develop the program for loading facility data sets and incorporate them into a mult-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 deploy and evaluate software. 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. Some knowledge of AI and ML principles and practices Ability to work collaboratively with a diverse team 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 Additional 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 The posting shall remain open until the position is filled, however for full consideration, please apply by close of business on October 22nd, 2020. 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. Full-time, M-F, exempt (monthly paid) from overtime pay. Salary for Postdoctoral positions depends on years of experience post-degree. 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. Learn About Us: Working at Berkeley Lab has many rewards including a competitive compensation program, excellent health and welfare programs, a retirement program that is second to none, and outstanding development opportunities. To view information about the many rewards that are offered at Berkeley Lab- Click Here. 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. 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.... - Permanent - Full-time
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