Intern - Machine Learning for Science

Position Overview:

The Machine Learning group at SLAC National Accelerator Laboratory is offering an internship for undergraduate and graduate students. The internship will focus on methodology and software development for sequential experimental design, with a strong focus on Bayesian methodology and neural network uncertainty quantification.

The objective of this internship is to give students an opportunity to gain valuable hands-on experience in machine learning/AI for science. Interns will develop practical machine learning skills in an applied, project-based setting, including development, implementation, and benchmarking of new methods, as well as the writing of reusable scientific software. This experience will not only enhance their skills and knowledge in the field but will also give them a boost when applying for jobs or graduate programs in the future. Interns will work as members of an existing research team, with regular presentation of results and direct technical supervision.

Specific responsibilities (include but are not limited to):

• Outline research plan for the duration of the internship in discussion with the research group, including overall targets and intermediate milestones.
• Review existing methodologies for neural network uncertainty quantification and identify opportunities for development.
• Research and develop quality metrics, in conjunction with the research group.
• Compare methodologies on existing datasets and summarize and present results.
• Integrate methods with existing Bayesian experimental design approaches.
• Deliver results as reusable software.

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 the physical sciences, applied mathematics, and software engineering.

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:

• Be pursuing a Bachelor's, Master's or Doctoral degree in a science, engineering or equivalent discipline.
• Have strong communication skills.
• Have the ability to work in a collaborative environment.
• Be passionate about machine learning/AI for science.
• Have prior experience in Python programming and machine learning.

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,

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Classification Title: SLAC Intern Students

Job code: 0901

Intern Level: II

The expected pay range for this position is $24.92 to $30.03 per hour. SLAC National Accelerator Laboratory/Stanford University provides pay ranges representing its good faith estimate of the hourly wage the university reasonably expects to pay for a position. 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.