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Research Associate - Machine Learning

  • ... Menlo Park, Capellen, United States
  • ... Full time
  • ... Salary: 100000 per year
  • Posted on: Feb 06, 2024       Expires on: Mar 22, 2024

Research Associate - Machine Learning   

JOB TITLE:

Research Associate - Machine Learning

JOB TYPE:

Full-time

JOB LOCATION:

Menlo Park Capellen United States

JOB DESCRIPTION:

SLAC Job Postings


Position overview:

SLAC National Accelerator Laboratory is seeking Research Associates with a proven track record of scientific achievement applying machine learning (ML) techniques and a background in material science, ultrafast x-ray sciences.

In this position, you will be supporting a research effort managed by the Linac Coherent Light Source (LCLS) and Laboratory Directed Research and Development (LDRD) program.
You will focus on develop a model to enable end-to-end alignment of electron probes that are integrated with 1-MHz LCLS-II.
This will expand the horizon of complex photoelectron spectrometers and capabilities.
Multi-lens configurable electron optics coupled with a state-of-the-art free electron laser will allow the exploration of exotic quantum materials, nanomaterials, and complex gas phase systems.
To reduce the time to alignment in this system, an end-to-end machine learning-directed model will be developed to automate the alignment of the electron optics.
Efforts here focus on a specific use case at LCLS-II.
The overall aim is to build digital twins of the spectrometers.
This will consist of a high-fidelity multi-physics model capable of describing the micro and macro features of the electron imaging lens.
Mirroring the state of and behavior of the physical system is a key goal of this project.
The research associate will also participate and expected to lead experiments at facilities.

Your specific duties include:

  • Develop machine learning-directed model to automate the alignment of the electron optics.
  • Conduct experiments and analysis of measurements on acquired from x-ray beam times on quantum materials at synchrotron and x-ray facilities.
  • Build advanced machine learning architectures, explore alternative center finding techniques - such as through Bayesian methods, Bayesian optimization, and other machine learning tools.
  • Analyze x-ray scattering, photoemission, and imaging measurements.

Note: The Research Associate role is a fixed term staff position.
Appointment duration is 12 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.

Preview of applications begins immediately.
Applications are accepted until the position is filled.
Interested candidates should submit a cover letter, CV, and three references to Quynh Nguyen (mailto:qlnguyen@slac.
stanford.
edu)

To be successful in this position you will bring:

  • Ph.
    D.
    in physical sciences (physics, chemistry, material science), Quantum information, Mathematics, computer science, computational science or engineering.
  • Experience in theoretical computations, machine learning, big data analysis
  • Experience with programming (Python, PyTorch/TensorFlow, C++, etc.
    )
  • Willingness to learn how to use open-source modeling platforms, analysis of big data.
  • Ability to carry out independent and collaborative research in a diverse research team.
  • Effective written and verbal communication skills.
    good interpersonal skills are essential.

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

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,

-

  • Classification Title: Research Assoc-Experimental
  • Grade: G, Job code: 0127
  • Employment Duration: Fixed term – 12 months

The expected pay range for this position is $70,000 - $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.

Position Details

POSTED:

Feb 06, 2024

EMPLOYMENT:

Full-time

SALARY:

100000 per year

SNAPRECRUIT ID:

S-1707480897-a67ac3c5135eefd9ea3981827303b937

LOCATION:

Capellen United States

CITY:

Menlo Park

Job Origin:

jpick2

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SLAC Job Postings


Position overview:

SLAC National Accelerator Laboratory is seeking Research Associates with a proven track record of scientific achievement applying machine learning (ML) techniques and a background in material science, ultrafast x-ray sciences.

In this position, you will be supporting a research effort managed by the Linac Coherent Light Source (LCLS) and Laboratory Directed Research and Development (LDRD) program. You will focus on develop a model to enable end-to-end alignment of electron probes that are integrated with 1-MHz LCLS-II. This will expand the horizon of complex photoelectron spectrometers and capabilities. Multi-lens configurable electron optics coupled with a state-of-the-art free electron laser will allow the exploration of exotic quantum materials, nanomaterials, and complex gas phase systems. To reduce the time to alignment in this system, an end-to-end machine learning-directed model will be developed to automate the alignment of the electron optics. Efforts here focus on a specific use case at LCLS-II. The overall aim is to build digital twins of the spectrometers. This will consist of a high-fidelity multi-physics model capable of describing the micro and macro features of the electron imaging lens. Mirroring the state of and behavior of the physical system is a key goal of this project. The research associate will also participate and expected to lead experiments at facilities.

Your specific duties include:

  • Develop machine learning-directed model to automate the alignment of the electron optics.
  • Conduct experiments and analysis of measurements on acquired from x-ray beam times on quantum materials at synchrotron and x-ray facilities.
  • Build advanced machine learning architectures, explore alternative center finding techniques - such as through Bayesian methods, Bayesian optimization, and other machine learning tools.
  • Analyze x-ray scattering, photoemission, and imaging measurements.

Note: The Research Associate role is a fixed term staff position. Appointment duration is 12 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.

Preview of applications begins immediately. Applications are accepted until the position is filled. Interested candidates should submit a cover letter, CV, and three references to Quynh Nguyen (mailto:qlnguyen@slac.stanford.edu)

To be successful in this position you will bring:

  • Ph.D. in physical sciences (physics, chemistry, material science), Quantum information, Mathematics, computer science, computational science or engineering.
  • Experience in theoretical computations, machine learning, big data analysis
  • Experience with programming (Python, PyTorch/TensorFlow, C++, etc.)
  • Willingness to learn how to use open-source modeling platforms, analysis of big data.
  • Ability to carry out independent and collaborative research in a diverse research team.
  • Effective written and verbal communication skills. good interpersonal skills are essential.

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

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,

-

  • Classification Title: Research Assoc-Experimental
  • Grade: G, Job code: 0127
  • Employment Duration: Fixed term – 12 months

The expected pay range for this position is $70,000 - $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.

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