al information go to <a href="http://www.lanl.gov/careers/career-options/postdoctoral-research/index.php">Postdoc Program </a>. </p><p class="MsoNormal" style="MARGIN: 0in 0in 0pt"></p><p class="MsoNormal" style="MARGIN: 0in 0in 10pt; LINE-HEIGHT: normal; mso-margin-top-alt: auto; mso-margin-bottom-alt: auto"><strong>
to Reeju Pokharel ( <a>reeju@lanl.gov </a>) </p><p class="MsoListParagraphCxSpMiddle" style="MARGIN: 0in 0in 0pt 0.5in; TEXT-INDENT: -0.25in; mso-list: l1 level1 lfo2">
ase send an email to <a href="mailto:applyhelp@lanl.gov">applyhelp@lanl.gov </a>or call 1-505-665-44

Los Alamos National Laboratory Adaptive Data Analysis Postdoc in Los Alamos, New Mexico

Vacancy Name: IRC70023

Description

Job Title Adaptive Data Analysis Postdoc

Location Los Alamos, NM, US

Organization Name MST-8/Materials Science in Radiation and Dynamic Extremes

What You Will Do

The Scattering Science Team of the Materials Science in Radiation and Dynamics Extremes Group (MST-8) group at Los Alamos National Laboratory is seeking for an outstanding postdoctoral candidate to develop adaptive data analysis framework utilizing machine learning methods coupled with mechanics and diffraction simulations to enable real-time data reconstruction during diffraction experiments at 3rd generation light sources such as the Advanced Photon Source (APS) and Cornell High Energy Synchrotron Source (CHESS). The successful candidate will work together with the PI to develop adaptive machine learning tools to decrease both measurement times and reconstruction times with the goal of achieving real-time (minutes – hours instead of weeks) feedback to enable adaptive and multimodal diffraction/imaging experiments at various light sources. This position also provides opportunities to collaborate with diverse set of researchers within LANL as well as at other national laboratories and universities.

Areas of particular interests are:

  • Understanding of scattering physics

  • Microstructure information extraction from diffraction/imaging data analysis.

  • Modeling/Simulation of mechanical properties of materials.

  • Experience handling large amounts of raw data from imaging and scattering experiments such as high-energy X-ray diffraction microscopy (HEDM), tomography (μ-CT), Bragg coherent X-ray diffraction Imaging (BCDI).

  • Development of data analysis software for diffraction data measured at light sources to gain as much insights from the measured data as possible

  • Implementation of machine learning methods for solving engineering problems

What You Need

Minimum Job Requirements:

  • Background in at least one of the following areas: materials science or physics with experience in performing experiments at synchrotron facilities, or computational materials science with experience dealing with microstructures and crystal plasticity simulations, or applied math/data science with experience developing machine learning models.

  • Proficient in writing code in Python.

  • Familiarity with open source libraries such as TensorFlow and Keras (or equivalent) to build machine learning models.

  • Experience in applying machine learning techniques to various physics problems.

  • Demonstrated ability to communicate both technically and interpersonally, both orally and in writing.

Desired Skills:

Desired Skills :

  • Understanding of influence of microstructure on properties and performance of materials.

  • Demonstrated ability to develop data analysis software for diffraction data measured at light sources.

  • Demonstrated ability to develop machine learning models for image analysis and familiarity with uncertainty quantification.

  • Experience in performing scattering experiments at national and/or international neutron and synchrotron X-ray user facilities.

  • Interest in travel to national and international neutron and synchrotron X-ray facilities to perform scattering experiments.

Education: A Ph.D. in engineering, materials science, physics, applied math, or closely related discipline, earned within the last five years.

Notes to Applicants :

  • In addition to applying online, interested candidates should send their inquiries, cover letter, CV including a list of peer-reviewed publications and invited/contributed talks, and the names and contact information of three references to Reeju Pokharel ( reeju@lanl.gov )

  • The cover letter should directly address the minimum job requirements and desired skills of this position, with specific examples from your academic and research experience.

  • To receive full consideration, please ensure that your application package provides all of the information requested above.

  • Evaluation of applications will commence immediately and continue until the position is filled.

Additional Details:

Position does not require a security clearance. Selected candidates will be subject to drug testing and other pre-employment background checks.

New-Employment Drug Test: The Laboratory requires successful applicants to complete a new-employment drug test and maintains a substance abuse policy that includes random drug testing.

Candidates may be considered for a Director's Postdoc Fellowship and outstanding candidates may be considered for the prestigious Richard P. Feynman, Darleane Christian Hoffman, J. Robert Oppenheimer, or Frederick Reines Distinguished Postdoc Fellowships.

For general information go to Postdoc Program .

Equal Opportunity:

Los Alamos National Laboratory is an equal opportunity employer and supports a diverse and inclusive workforce. All employment practices are based on qualification and merit, without regards to race, color, national origin, ancestry, religion, age, sex, gender identity, sexual orientation or preference, marital status or spousal affiliation, physical or mental disability, medical conditions, pregnancy, status as a protected veteran, genetic information, or citizenship within the limits imposed by federal laws and regulations. The Laboratory is also committed to making our workplace accessible to individuals with disabilities and will provide reasonable accommodations, upon request, for individuals to participate in the application and hiring process. To request such an accommodation, please send an email to applyhelp@lanl.gov or call 1-505-665-4444 option 1.

Where You Will Work

Located in northern New Mexico, Los Alamos National Laboratory (LANL) is a multidisciplinary research institution engaged in strategic science on behalf of national security. LANL enhances national security by ensuring the safety and reliability of the U.S. nuclear stockpile, developing technologies to reduce threats from weapons of mass destruction, and solving problems related to energy, environment, infrastructure, health, and global security concerns.

What You Will Do

The Scattering Science Team of the Materials Science in Radiation and Dynamics Extremes Group (MST-8) group at Los Alamos National Laboratory is seeking for an outstanding postdoctoral candidate to develop adaptive data analysis framework utilizing machine learning methods coupled with mechanics and diffraction simulations to enable real-time data reconstruction during diffraction experiments at 3rd generation light sources such as the Advanced Photon Source (APS) and Cornell High Energy Synchrotron Source (CHESS). The successful candidate will work together with the PI to develop adaptive machine learning tools to decrease both measurement times and reconstruction times with the goal of achieving real-time (minutes – hours instead of weeks) feedback to enable adaptive and multimodal diffraction/imaging experiments at various light sources. This position also provides opportunities to collaborate with diverse set of researchers within LANL as well as at other national laboratories and universities.

Areas of particular interests are:

  • Understanding of scattering physics

  • Microstructure information extraction from diffraction/imaging data analysis.

  • Modeling/Simulation of mechanical properties of materials.

  • Experience handling large amounts of raw data from imaging and scattering experiments such as high-energy X-ray diffraction microscopy (HEDM), tomography (μ-CT), Bragg coherent X-ray diffraction Imaging (BCDI).

  • Development of data analysis software for diffraction data measured at light sources to gain as much insights from the measured data as possible

  • Implementation of machine learning methods for solving engineering problems

Appointment Type Postdoc

Postdoc

Minimum Salary

Maximum Salary

Contact Details

Contact Name

Email

Work Telephone

Req ID: IRC70023

The Laboratory is also committed to making our workplace accessible to individuals with disabilities and will provide reasonable accommodations, upon request, for individuals to participate in the application and hiring process.

To request a disability accommodation,
email applyhelp@lanl.gov or call (505) 665-4444, option 1.

DirectEmployers