Position Overview: \n
The Stanford Synchrotron Radiation Lightsource (SSRL) at SLAC National Accelerator Laboratory, a national scientific user facility, seeks a Head of Data, Compute, Automation, and AI (DCAA) to lead a new facility-wide effort supporting operations and research across both experimental stations and accelerator systems. SSRL supports a broad range of scientific user programs in chemistry, materials science, environmental science, structural biology, and crystallography through advanced X-ray techniques and operation of a diverse set of beamlines based on the SPEAR3 storage ring.
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The position requires demonstrated experience leading multidisciplinary teams and delivering complex, facility-scale technical initiatives in scientific or data-intensive environments.
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The DCAA effort will focus on strengthening shared capabilities across data handling, compute access, and workflow integration, building on existing expertise across both experimental and accelerator environments. The objective is to improve consistency, usability, and efficiency in how data, analysis, and workflows are handled in practice, while enabling more immediate feedback during experiments and supporting increasingly complex and data-intensive scientific workflows, including more adaptive and feedback-driven experimental approaches.
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The DCAA Head will build, mentor, and lead a high-performing multidisciplinary team working in close collaboration with SSRL staff scientists, engineers, technical staff, and computing teams. The role focuses on identifying common needs across techniques and systems and translating them into practical, reusable solutions that reduce duplicated effort while remaining flexible enough to support science-, technique-, and system-specific requirements.
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The position includes setting priorities and guiding technical direction in close coordination with SSRL division leadership to ensure alignment with facility-wide goals and scientific programs. The DCAA Head will serve as a central coordination point for data, compute, automation, and AI-related activities across SSRL, working across organizational boundaries.
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The role will also serve as a visible representative of SSRL in interactions with SLAC leadership and DOE-level data and computing initiatives, including ASCR and emerging national platforms such as the American Science Cloud, ensuring strong engagement and leadership presence in these efforts.
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This is an SSRL-level leadership role with direct impact on experimental workflows, accelerator data utilization, and the overall effectiveness of SSRL operations.
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Your specific responsibilities include:\n
\n - Lead and coordinate the development and execution of a facility-wide approach to data, compute, automation, and workflow integration.
\n - Build, mentor, and manage a multidisciplinary team spanning data architecture, software engineering, controls/automation, and compute integration.
\n - Guide the development and deployment of shared solutions for metadata capture, data organization, workflow orchestration, and analysis tools that support both experimental stations and accelerator use cases.
\n - Work in close coordination with SSRL division directors and facility staff to align priorities, scope efforts, and ensure that DCAA activities support scientific and operational objectives.
\n - Establish and maintain reliable and supported pathways for data movement, storage, and analysis, while serving as a visible representative of SSRL in DOE computing initiatives, including ASCR and national platforms such as the American Science Cloud, ensuring strong engagement and leadership presence in these efforts.
\n - Oversee the development of automation, first-pass analysis workflows, and real-time feedback capabilities that improve experimental efficiency and data accessibility across the facility.
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To be successful in this position you will bring:\n
\n - An advanced degree (minimum Master's, PhD preferred) in a relevant field such as physics, chemistry, materials science, computer science, engineering, or a related discipline.
\n - Demonstrated experience leading technical teams and delivering complex projects in scientific, engineering, or data-intensive environments.
\n - A strong background in either scientific research or computational/data systems, with the ability to operate effectively at the interface between experimental workflows and computing infrastructure.
\n - Experience working in, or closely with, experimental or facility environments, with an understanding of operational constraints, user-facing workflows, and the need for reliable, production-level solutions.
\n - Proven ability to translate diverse and sometimes competing requirements into practical, scalable approaches that can be adopted across multiple teams and use cases.
\n - Experience coordinating efforts across organizational boundaries and working effectively with scientists, engineers, and computing professionals at different levels of expertise.
\n - Strong communication, collaboration and leadership skills, including the ability to guide technical direction, build alignment across stakeholders, and represent activities at the institutional or national level.
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SLAC Manager Competencies:\n
\n - Results Through Others (drives results & directs work): Achieves expected results by effectively delegating and managing the work of others.
\n - Aligns Priorities (plans & aligns): Ensures planning and prioritization of resources and work efforts; ensures alignment of direct and matrix reports to support organizational goals and business plans.
\n - Applies Lab Acumen (business insight): Maintains understanding of lab efforts and direction as well as current research and trends, considers technology and customer impacts, and contributes relevant, informed ideas to lab growth.
\n - Navigates Complexity (managing complexity): Manages a multitude of information and complex circumstances to discern what is most important; demonstrates effective problem-solving, decision-making, and takes appropriate action, even in difficult situations or with conflicting data.
\n - Builds Trust (instills trust): Earns trust and credibility from team members, peers and stakeholders; demonstrates SLAC values of respect and integrity.
\n - Relationships (interpersonal savvy, collaborates, manages conflict, builds networks): Builds relationships to foster trust, collaboration, and a positive climate to achieve team, department/directorate and lab goals.
\n - Communication (communicates effectively): Ensures effective information flow to various audiences; delivers clear and appropriate written and verbal communications; makes clear and impactful presentations to a variety of internal and external audiences.
\n - Self-Awareness (demonstrates self-awareness): Seeks feedback from others and takes ownership of, and actions to address what is learned; recognizes impact on others and adjusts as needed; pursues continuous learning opportunities; implements a meaningful development plan.
\n - Team Effectiveness (builds effective teams): Effectively motivates team members and fosters a diverse and collaborative team environment; leverages team members strengths for overall team effectiveness; incorporates insights to improve team operations.
\n - Purpose & Vision (drives vision & purpose): Articulates a clear vision of expected outcomes; inspires others to execute work plans and feel a sense of purpose and ownership for the mission.
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Physical requirements and working conditions:\n
\n - Consistent with its obligations under the law, the University will provide reasonable accommodation to any employee with a disability who requires accommodation to perform the essential functions of the job.
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Work standards:\n
\n - Interpersonal Skills: Demonstrates the ability to work well with Stanford colleagues and clients and with external organizations.
\n - Promote Culture of Safety: Demonstrates commitment to personal responsibility and value for environment, safety and security; communicates related concerns; uses and promotes safe behaviors based on training and lessons learned. Meets the applicable roles and responsibilities as described in the ESH Manual, Chapter 1 General Policy and Responsibilities:
\n - Subject to and expected to comply with all applicable University policies and procedures, including but not limited to the personnel policies and other policies found in the University's Administrative Guide,
\n - As a national laboratory, SLAC National Accelerator Laboratory is responsible for adhering to the Homeland Security Presidential Directive 12 (HSPD-12) and Department of Energy (DOE) Order 473.1A, which require employees to obtain and maintain a HSPD-12 Personal Identity Verification (PIV) Credential. To obtain this credential, employees must successfully complete the applicable tier of federal background investigation post hire and receive a favorable federal adjudication. The tier of federal background investigation will be determined by job duties and national security or public trust responsibilities associated with the job. All tiers of investigation include a declaration of illegal drug activities, including use, supply, possession, or manufacture within the last 1 to 7 years (depending on the applicable tier of investigation). Illegal drug activities include marijuana and cannabis derivatives
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\n - Classification Title: Research Technical Manager 3
\n - Grade: N, Job Code: 4988
\n - Duration: Continuing
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The expected pay range for this position is $229,608 - $276,025 per annum .
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SLAC National Accelerator Laboratory/Stanford University provides pay ranges representing its good faith estimate of the salary or hourly wage the university reasonably expects to pay for a position upon hire. The pay offered to a selected candidate will be determined based on factors such as (but not limited to) the scope and responsibilities of the position, the qualifications of the selected candidate, departmental budget availability, internal equity, geographic location, and external market pay for comparable jobs.
At SLAC/Stanford, base pay represents only one aspect of the comprehensive rewards package.
