Computational Materials Scientist - Postdoctoral Researcher

LLNL$123K *
Manufacturing & Automotive
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • PhD in materials science, metallurgy, condensed matter physics, applied math, or a closely related field.
  • Ability to secure a U.S. DOE Q-level security clearance, requiring U.S. citizenship.
  • Knowledge in CALPHAD, microstructure modeling, uncertainty quantification, ICME, alloy design, and design of experiments.
  • Demonstrated experience in scientific research software development.
  • Proficiency in thermodynamic software like Thermo-Calc or open-source alternatives for CALPHAD database development.
  • Understanding of thermodynamics, phase stability, phase transformations, defect structures, solidification, and thermo-mechanical processing.
  • Strong communication skills with a solid publication record.

Responsibilities

  • Develop multicomponent thermodynamic and kinetic databases for inorganic systems.
  • Integrate ICME microstructure evolution models into the Materials Acceleration Platform.
  • Implement uncertainty quantification methods in ICME.
  • Collaborate with experimentalists to design experiments and develop materials.
  • Publish findings in peer-reviewed journals and present at conferences.
  • Engage with a multidisciplinary team to achieve program goals.
  • Perform additional duties as assigned.

Benefits

  • Opportunities for research publication and conference presentations.
  • Work within a leading national laboratory for advanced materials research.
  • Engage in innovative projects in a multidisciplinary team environment.
Full Job Description
Job Description

We have an opening for a Postdoctoral Researcher to work in the field of computational materials science and actively participate in research dedicated to the discovery of new structural alloys for extreme environments. You will be involved in research to implement methods for materials design and process development. You will be a creative force in the integration and application of thermodynamic and kinetic models into an alloy design framework (including material properties models) that uses numerical optimization methods to rapidly screen for promising compositions over vast multi-component phase spaces. This position is in the Actinide and Lanthanide Science group within the Materials Science Division.

In this role you will
  • Independently develop multicomponent thermodynamic and kinetic databases for inorganic (metal, oxide, carbide, hydride, etc.) systems.
  • Incorporate new Integrated Computational Materials Engineering (ICME) microstructure evolution models and resulting property predictions (ranging from analytical to machine learning surrogate models) in LLNL's Materials Acceleration Platform that is deployed on LLNL's High Performance Computing infrastructure.
  • Develop uncertainty quantification (UQ) and propagation methods into ICME approaches.
  • Interface with experimentalists in design of experiment and material development campaigns.
  • Work both independently and collaborate with others in a multidisciplinary team environment to accomplish program goals.
  • Publish research results in peer-reviewed scientific journals and present results at external conferences, seminars, and technical meetings.
  • Perform other duties as assigned.

Qualifications
  • Ability to secure and maintain a U.S. DOE Q-level security clearance which requires U.S. citizenship.
  • PhD in materials science, metallurgy, condensed matter physics, applied math, or a closely related field.
  • Experience and knowledge in at least three of the following areas: CALPHAD, microstructure and property modeling, uncertainty quantification and propagation, ICME, alloy design, design of experiments.
  • Demonstrated ability to independently develop or make significant contributions to scientific research software.
  • Experience with commercial (Thermo-Calc, Pandat, or FactSage) or open source (PyCalphad, Thermochimica, or OpenCalphad) computational thermodynamics software to perform CALPHAD database development.
  • Experience in at least twoof the following metallurgy topics: thermodynamics, phase stability, phase transformations, defect structures, solidification, or thermo-mechanical processing.
  • Proficient verbal and written communication skills as reflected in effective presentations at meetings and a demonstrated strong publication record.
  • Initiative and interpersonal skills with desire and ability to work in a collaborative, multidisciplinary team environment.

Qualifications We Desire
  • Experience with artificial intelligence (AI) and/or machine learning (ML) methods.
  • Experience with algorithms relevant for materials design and discovery (Bayesian Optimization, black-box optimization, gradient-based optimization).
  • Experience parameterizing or developing numerical methods for thermodynamic and/or kinetic modeling of phase transformations and microstructure evolution (e.g. CALPHAD, Kampmann-Wagner numerical method, phase field, cellular automata, Monte Carlo method, continuum models).
  • Direct experience with alloy synthesis, processing, and/or characterization; or extensive experience collaborating with experimental colleagues.

Pay Range

$123,048 Annually

This is the lowest to highest salary we in good faith believe we would pay for this role at the time of this posting. An employee's position within the salary range will be based on several factors including, but not limited to, specific competencies, relevant education, qualifications, certifications, experience, skills, seniority, geographic location, performance, and business or organizational needs.

Additional Information

All your information will be kept confidential according to EEO guidelines.

Position Information

This is a Postdoctoral appointment with the possibility of extension to a maximum of three years, open to those who have been awarded a PhD at time of hire date.

Security Clearance

This position requires a Department of Energy (DOE) Q-level clearance.If you are selected, wewill initiate a Federal background investigation to determine if youmeet eligibility requirements for access to classified information or matter. Also, all L or Q cleared employees are subject to random drug testing. Q-level clearance requires U.S. citizenship.

Pre-Employment Drug Test

External applicant(s) selected for this position must pass a post-offer, pre-employment drug test. This includes testing for use of marijuana as Federal Law applies to us as a Federal Contractor.

Wireless and Medical Devices

Per the Department of Energy (DOE), Lawrence Livermore National Laboratory must meet certain restrictions with the useand/or possession ofmobile devices in Limited Areas. Depending on your job duties, you may be required to work in a Limited Area whereyou are not permitted to have a personal and/or laboratory mobile devicein your possession. This includes, but not limited to cell phones, tablets, fitness devices, wireless headphones, and other Bluetooth/wireless enabled devices.

Ifyou useamedical device, whichpairs with a mobile device,you must still follow the rules concerningthe mobile device in individual sections within Limited Areas. Sensitive Compartmented Information Facilities requireseparate approval. Hearing aids without wireless capabilities or wireless that has been disabled are allowed in Limited Areas, Secure Space and Transit/Buffer Space within buildings.

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