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SLAC National Accelerator Laboratory in Menlo Park seeks an Associate Staff Scientist in the LCLS Biological Sciences Department to advance structural biology research with advanced computational workflows.
You will support the MFX instrument, develop data-driven analysis, and lead community outreach while collaborating across scientists, engineers, and users to enhance beamline operations.
SLAC National Accelerator Laboratory (SLAC) is one of the world’s premier research laboratories, providing internationally leading capabilities through its accelerator based light sources and scientific programs. The Linac Coherent Light Source (LCLS), a directorate of SLAC and the world’s first hard X ray free electron laser, seeks an Associate Staff Scientist with expertise in structural biology, scientific computing, data science, scientific outreach, and user facility operations. The successful candidate will join the LCLS Biological Sciences Department within the Science Research and Development Division and contribute to the operation, scientific advancement, and development of the biology user program.
The Associate Staff Scientist will play a leading role in supporting user science activities primarily at the Macromolecular Femtosecond Crystallography (MFX) instrument and its LCLS II upgrade, MFX HE. The position combines user support, scientific software development, computational methods, data science, scientific outreach, community engagement, and collaborative research. Working closely with scientists, engineers, software developers, and users, the candidate will develop innovative approaches that improve the robustness, reliability, efficiency, data quality, scientific productivity, and the overall user experience.
A major focus of the position will be the development and deployment of advanced computational tools and workflows for structural biology experiments, including automated data processing, real time experiment feedback, data visualization, artificial intelligence enabled analysis, and data driven experimental strategies. The successful candidate will help shape the next generation of structural biology capabilities at LCLS by integrating advances in computation, automation, machine learning, and data science into beamline operations and user workflows. The position offers the opportunity to serve as a computational beamline scientist, bridging scientific software development, experimental operations, and biological discovery.
The position also includes a significant leadership role in community engagement and scientific outreach. The successful candidate will work closely with users and collaborators to lower barriers to access, improve user readiness, and foster a vibrant and engaged scientific community around MFX and future LCLS biological sciences capabilities. This role involves close collaboration with internal staff and external user groups, supporting experiment planning, execution, and analysis while driving technical innovation that enhances LCLS capabilities. Dissemination of scientific results through peer reviewed publications, conference presentations, workshops, invited talks, and community engagement activities is expected. The work will be performed as part of a highly collaborative team of scientists at SLAC and partner institutions.
Applicants must provide evidence of a PhD. Applicants should also include a cover letter, a research statement describing their scientific interests and accomplishments, a curriculum vitae, and a publication list. Letters of recommendation or contact information for references are welcomed but not required at the time of application.
SLAC is a U.S. Department of Energy (DOE) laboratory operated by Stanford University and based in Menlo Park, CA.
This position is posted at the Associate Staff Scientist level. The Associate Scientist position is a 3-5 year fixed-termposition and the entry level in the Staff Scientist career path. The Associate Scientist position is scheduled to be assessed after the 3-5 year period, with the possibility of appointment to the Staff Scientist level.