Intern - Computer Science

Position Overview:

SLAC National Accelerator Laboratory seeks a talented graduate student intern within the Instrumentation Division of the Technology Innovation Directorate. This department is responsible for delivering and supporting instrumentation for many of SLAC¿s scientific programs. In this role, you will work side by side with leading scientific and engineering teams while contributing to R&D on future approaches and technologies for detector and instrumentation systems. We work on complex system design spanning concept, design, testing, commissioning, operation, and maintenance of high-speed data acquisition and electrical control systems for research instrumentation.

Some of our current key projects include the Linac Coherent Light Source (LCLS) X-ray laser and high-speed X-ray detectors, FACET high-energy electron accelerator, Cosmic Microwave Background Stage 4 (CMB-S4) telescope array (to be deployed in the Andes and the South Pole), Next Enriched Xenon Observatory (nEXO), Light Dark Matter eXperiment (LDMX), Cryogenic Dark Matter Search (CDMS), and development of flight hardware for future space telescopes.

This internship supports Morpheus, a project exploring machine-learning-based methods toward self-calibrating X-ray cameras for LCLS. The intern will use real detector data and associated metadata to assess what is achievable over a summer timeframe, develop baseline approaches, and build software proof of concept for automated calibration and/or performance monitoring. This project provides experience in scientific computing, ML for sensor data, and analysis workflows that directly impact the performance and reliability of next-generation X-ray imaging systems at LCLS.

At the conclusion of the summer, results will be documented and presented to help determine subsequent steps for this R&D effort.

Specific responsibilities (include but are not limited to):

• Review existing X-ray camera calibration and monitoring workflows; identify candidate signals/features for automation.
• Assemble, clean, and curate datasets from detector data and associated metadata (configuration, operating conditions, etc.).
• Develop and evaluate ML methods to estimate calibration parameters and/or detect drift, anomalies, or performance degradation.
• Build reproducible training and evaluation pipelines in Python, including validation strategies and quantitative metrics.
• Deliver a documented proof-of-concept workflow (e.g., notebooks and/or a small Python package) suitable for follow-on integration.
• Present results and recommendations at the end of the internship.

Opportunities and Benefits

• Growth and mentorship from exceptionally talented engineers and scientists from SLAC and Stanford University.
• A mission-driven, stable, collaborative, highly interdisciplinary, and supportive work environment.
• Opportunity to experience a multidisciplinary research environment, integrating knowledge from many subject areas spanning computer engineering, physical sciences, applied mathematics, and software applications.

Note: This is an hourly, non-benefits eligible temporary-nonexempt, internship position (work at 50% full-time equivalent or more), not to exceed 980 hours in six consecutive months.

Eligible applicants must be at least 18 years of age, currently enrolled in an educational program or recently graduated, and have US work authorization.

To be successful in this position, candidates should:

• Demonstrates initiative and the ability to work independently as well as part of a team.
• Attention to detail.
• Strong problem-solving skills.
• Enthusiasm for contributing to scientific research.
• Commitment to contributing positively to a team-oriented workplace.

In addition, preferred requirements include:

• Strong Python skills (NumPy, pandas; PyTorch/TensorFlow a plus).
• Familiarity with ML fundamentals and model validation.
• Experience with noisy real-world data and building robust pipelines.
• Interest in scientific instrumentation, imaging sensors, or experimental data.
• Good communication skills and ability to work in a collaborative research environment.

SLAC Employee Competencies:

• Effective Decisions: Uses job knowledge and solid judgment to make quality decisions in a timely manner.
• Self-Development: Pursues a variety of venues and opportunities to continue learning and developing.
• Dependability: Can be counted on to deliver results with a sense of personal responsibility for expected outcomes.
• Initiative: Pursues work and interactions proactively with optimism, positive energy, and motivation to move things forward.
• Adaptability: Flexes as needed when change occurs, maintains an open outlook while adjusting and accommodating changes.
• Communication: Ensures effective information flow to various audiences and creates and delivers clear, appropriate written, spoken, presented messages.
• Relationships: Builds relationships to foster trust, collaboration, and a positive climate to achieve common goals.

Physical requirements and working conditions:

• 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.

Work Standards:

• Interpersonal Skills: Demonstrates the ability to work well with Stanford colleagues and clients and with external organizations.
• 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:
• 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,
• 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, which are still considered illegal under federal law, regardless of state laws.

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• Classification Title: SLAC Intern Students [Level I ¿ III]
• Job Code: 0901
• Employment Duration: 12 weeks

The expected pay range for this position is $31.02 ¿ $39.26 per hour.

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.