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Research Assoc-Experimental - Artificial Intelligence and Machine Learning

Job ID

5985

Location

SLAC - Menlo Park, CA

Full-Time

Temporary

SLAC Job Postings

Positions overview:

The Stanford Synchrotron Radiation Lightsource at SLAC National Accelerator Laboratory has an opening for a Research Associate (RA) with research interests in developing artificial intelligence and machine learning (AI/ML) approaches to guide synchrotron x-ray characterization, particularly in-situ and operando measurements at the beamline. The RA will also help support the X-ray scattering program at SSRL (roughly 50%). User support will involve coordinating with users in order to understand their scientific objectives, helping them to design characterization approaches which are able to address these objectives, on-boarding and training users on the beamline instrumentation, and training users on the data reconstruction and interpretation. A unique component of this user support role will be implementing AI/ML approaches for human in the loop and/or autonomous data interpretation into the general user program and working collaboratively with user groups to bridge their scientific questions and these new methods.

The goal of the project is to extend existing codebases, as well as develop novel approaches to utilize machine learning for the autonomous interpretation of x-ray scattering data. Of particular interest will be the development of approaches which are robust to non-idealities inherent to complex in-situ and operando x-ray characterization of materials synthesis or device operation. Additionally, there will be the opportunity to develop active learning strategies for the autonomous or human in the loop design of experiment to increase the impact of in-situ or operando characterization approaches. The RA will have the opportunity to publish lead-author manuscripts and to build a career in X-ray science, materials and/or data science, or a future teaching career.

Note: The Research Associate role is a fixed term staff position. Appointment duration is 24 months, with the possibility of extension. Assignment duration is contingent upon project needs and funding.

Applicants must provide evidence of either a recently completed PhD degree or confirmation of completion of the PhD degree requirements prior to starting the position. Applicants should also include a cover letter, a curriculum vitae which includes a list of publications, and names of three references for future letters of recommendation with the application.

To be successful in this position you will bring:

• PhD in physics, mathematics, computer science, engineering, materials sciences, chemistry, or related field.

• Demonstrated experience with x-ray characterization methods.

• Fundamental knowledge of the physics of x-ray scattering.

• Strong experimental, analytical and computation skills. Preferably experience analyzing large datasets using python or similar analysis tools.

• Expertise with machine learning packages such as Scikit-learn, TensorFlow,and/or PyTorch.

• Broad scientific interests and willingness to learn new skills.

• Effective written and verbal communication skills.

• Ability to work and communicate effectively with a diverse population; good interpersonal skills are essential.

• Ability to work independently and in a team 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 his or her job.

• Given the nature of this position, SLAC will require onsite work.

Work standards:

• Interpersonal Skills: Demonstrates the ability to work well with Stanford/SLAC 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: http://www-group.slac.stanford.edu/esh/eshmanual/pdfs/ESHch01.pdf

• 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, http://adminguide.stanford.edu Policies found in the University's Administrative Guide, http://adminguide.stanford.edu.

• Classification Title: Research Associate Experimental

• Job code: 0127, Grade: G

• Employment Duration: Fixed term – 24 months

The expected pay range for this position is $70,000 to $100,000 per annum. SLAC National Accelerator Laboratory/Stanford University provides pay ranges representing its good faith estimate of what 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.

SLAC National Accelerator Laboratory is an Affirmative Action / Equal Opportunity Employer and supports diversity in the workplace. All employment decisions are made without regard to race, color, religion, sex, national origin, age, disability, veteran status, marital or family status, sexual orientation, gender identity, or genetic information. All staff at SLAC National Accelerator Laboratory must be able to demonstrate the legal right to work in the United States. SLAC is an E-Verify employer.