Post-Doctoral focused on uncertainty quantification applied to constitutive models
- Req. Number: IRC135362
- Organization : MST-8/Structure/Property Relations
- City, State: Los Alamos, New Mexico
What You Will Do
The Materials Science and Technology division at Los Alamos National Laboratory has great opportunities for post doc candidates to join a team in the field of materials modeling, particularly uncertainty quantification methods and algorithms associated to models for the mechanical performance of metals.
You will work in conjunction with a team of staff scientists and graduate students. This position includes significant freedom in terms of specific research direction. In general, you will perform research to develop robust, physically realizable, and operationally valuable methods and algorithms to quantify and reduce the uncertainty of polycrystal constitutive models. The work will aim to (i) automatically calibrate and validate constitutive models for the mechanical performance of metals subjected to extreme environments, (ii) develop active learning schema, (iii) propose new design of experiments.
You should have a strong publication record, an interdisciplinary research philosophy, and the ability to effectively communicate with researchers with varied backgrounds. As a postdoctoral research associate, you will be given the opportunity to publish results in high-impact peer-reviewed journals and to present at well-known conferences. The position is for two years, with a third year possible based on performance and funding.
The successful candidate will join the 'Dynamic and Quasi-static loading - modeling (DQSLM)' team, which focuses on the development and use of advanced computational mechanics models to predict the effects of extreme and complex environments on both mechanical response and microstructure evolution in materials. The environments considered include high stresses, temperatures, radiation, etc. The DQSLM team adopts both hierarchical and integrated multiscale modeling and characterization strategies for mechanical deformation problems in the Material Science and Technology division.
What You Need
Minimum Job Requirements:
Education/Experience: Ph.D. in computer science, applied mathematics, statistics, physics, materials science, or related discipline completed within the last 5 years. Applications from candidates who will earn their degree by the time of appointment are accepted
Desired Qualifications:
Education/Experience: Ph.D. in computer science, applied mathematics, statistics, physics, materials science, or related discipline completed within the last 5 years. Applications from candidates who will earn their degree by the time of appointment are accepted
Desired Qualifications:
What You Need
Minimum Job Requirements:
Education/Experience: Ph.D. in computer science, applied mathematics, statistics, physics, materials science, or related discipline completed within the last 5 years. Applications from candidates who will earn their degree by the time of appointment are accepted
Desired Qualifications:
Work Location: The work location for this position is onsite and located in Los Alamos, NM. All work locations are at the discretion of management.
Salary: Competitive salaries are based on the date the PhD degree requirements were completed or the degree was awarded. Starting salary for a new graduate is currently $94,500. For more information go to Postdoc Program website at https://www.lanl.gov/careers/career-options/postdoctoral-research/index.php
Note to Applicants:
Located in beautiful northern New Mexico, Los Alamos National Laboratory (LANL) is a multidisciplinary research institution engaged in strategic science on behalf of national security. Our generous benefits package includes:
§ PPO or High Deductible medical insurance with the same large nationwide network
§ Dental and vision insurance
§ Free basic life and disability insurance
§ Paid childbirth and parental leave
§ Award-winning 401(k) (6% matching plus 3.5% annually)
§ Learning opportunities and tuition assistance
§ Flexible schedules and time off (PTO and holidays)
§ Onsite gyms and wellness programs
§ Extensive relocation packages (outside a 50 mile radius)
Additional Details
Directive 206.2 - Employment with Triad requires a favorable decision by NNSA indicating employee is suitable under NNSA Supplemental Directive 206.2. Please note that this requirement applies only to citizens of the United States. Foreign nationals are subject to a similar requirement under DOE Order 142.3A.
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. Although New Mexico and other states have legalized the use of marijuana, use and possession of marijuana remain illegal under federal law. A positive drug test for marijuana will result in termination of employment, even if the use was pre-offer.
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 regard 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
How to Apply: How to Apply: Login to Your Account to Complete the Application Process
Click the Vacancy Name number (in blue) to view any job's details.
• Click Apply or Add to Basket to apply later. Tip: To apply for a job or save your basket, you must have a LANL jobs account. Instructions on How to Activate/Create a LANL Jobs Account:
Follow the instructions below if you have ever had an employee Z number, been a contractor, or received Los Alamos Lab insurance coverage to activate your account:
• Select the Click Here button if you have been employed with the Lab or received insurance coverage.
• Please enter only your first and last name and current email address (an email with your validation code will be sent to you) to activate the account currently in our system.
• Enter your validation code as described in the email you receive and complete the 3-page registration form. Your account is now active, and you can apply for jobs or save to your basket. Important: Enter the validation code within 15 days to activate your account or your account will be deactivated
Follow the instructions below if you if you have never been employed with the Lab or received insurance coverage to create an account:
• Select the Register button if you have never been employed with the Lab or received insurance coverage to Create an Account.
• From here, you will establish an account with username and password
How to Apply: How to Apply: Login to Your Account to Complete the Application Process
Click the Vacancy Name number (in blue) to view any job's details.
• Click Apply or Add to Basket to apply later. Tip: To apply for a job or save your basket, you must have a LANL jobs account.
If you experience any technical issues, please email applyhelp@lanl.gov for assistance.
The Materials Science and Technology division at Los Alamos National Laboratory has great opportunities for post doc candidates to join a team in the field of materials modeling, particularly uncertainty quantification methods and algorithms associated to models for the mechanical performance of metals.
You will work in conjunction with a team of staff scientists and graduate students. This position includes significant freedom in terms of specific research direction. In general, you will perform research to develop robust, physically realizable, and operationally valuable methods and algorithms to quantify and reduce the uncertainty of polycrystal constitutive models. The work will aim to (i) automatically calibrate and validate constitutive models for the mechanical performance of metals subjected to extreme environments, (ii) develop active learning schema, (iii) propose new design of experiments.
You should have a strong publication record, an interdisciplinary research philosophy, and the ability to effectively communicate with researchers with varied backgrounds. As a postdoctoral research associate, you will be given the opportunity to publish results in high-impact peer-reviewed journals and to present at well-known conferences. The position is for two years, with a third year possible based on performance and funding.
The successful candidate will join the 'Dynamic and Quasi-static loading - modeling (DQSLM)' team, which focuses on the development and use of advanced computational mechanics models to predict the effects of extreme and complex environments on both mechanical response and microstructure evolution in materials. The environments considered include high stresses, temperatures, radiation, etc. The DQSLM team adopts both hierarchical and integrated multiscale modeling and characterization strategies for mechanical deformation problems in the Material Science and Technology division.
What You Need
Minimum Job Requirements:
- Strong programming skills required, along with either (A) experience with machine learning frameworks and data analysis; or (B) expertise in Bayesian inference drive method
- Excellent presentation, oral and written communication skills.
- Track record of peer-reviewed publications and presentations in your home discipline.
- Excellent interpersonal, oral and written communications skills.
- Strong publication record.
Education/Experience: Ph.D. in computer science, applied mathematics, statistics, physics, materials science, or related discipline completed within the last 5 years. Applications from candidates who will earn their degree by the time of appointment are accepted
Desired Qualifications:
- Experience with uncertainty quantification methods.
- Experience with machine learning systems and methods.
- Demonstrated experience in interdisciplinary science, especially in the areas mentioned above.
- Operational experience with national defense applications, technology development, and acquisition
What You Need
Minimum Job Requirements: - Strong programming skills required, along with either (A) experience with machine learning frameworks and data analysis; or (B) expertise in Bayesian inference drive method
- Excellent presentation, oral and written communication skills.
- Track record of peer-reviewed publications and presentations in your home discipline.
- Excellent interpersonal, oral and written communications skills.
- Strong publication record.
Education/Experience: Ph.D. in computer science, applied mathematics, statistics, physics, materials science, or related discipline completed within the last 5 years. Applications from candidates who will earn their degree by the time of appointment are accepted
Desired Qualifications:
- Experience with uncertainty quantification methods.
- Experience with machine learning systems and methods.
- Demonstrated experience in interdisciplinary science, especially in the areas mentioned above.
- Operational experience with national defense applications, technology development, and acquisition
What You Need
Minimum Job Requirements:
- Strong programming skills required, along with either (A) experience with machine learning frameworks and data analysis; or (B) expertise in Bayesian inference drive method
- Excellent presentation, oral and written communication skills.
- Track record of peer-reviewed publications and presentations in your home discipline.
- Excellent interpersonal, oral and written communications skills.
- Strong publication record.
Education/Experience: Ph.D. in computer science, applied mathematics, statistics, physics, materials science, or related discipline completed within the last 5 years. Applications from candidates who will earn their degree by the time of appointment are accepted
Desired Qualifications:
- Experience with uncertainty quantification methods.
- Experience with machine learning systems and methods.
- Demonstrated experience in interdisciplinary science, especially in the areas mentioned above.
- Operational experience with national defense applications, technology development, and acquisition
Work Location: The work location for this position is onsite and located in Los Alamos, NM. All work locations are at the discretion of management.
Salary: Competitive salaries are based on the date the PhD degree requirements were completed or the degree was awarded. Starting salary for a new graduate is currently $94,500. For more information go to Postdoc Program website at https://www.lanl.gov/careers/career-options/postdoctoral-research/index.php
Note to Applicants:
- As part of the online application process, please include a cover letter describing your professional interests, career goals, and related skills and qualifications.
- In addition to the application process, please email resume to laurent@lanl.gov
- No applicant is expected to have all the desired skills. Anyone who meets the education and minimum job requirements is encouraged to apply
- The work location for this position is onsite and located in Los Alamos, NM. All work locations are at the discretion of management.
Located in beautiful northern New Mexico, Los Alamos National Laboratory (LANL) is a multidisciplinary research institution engaged in strategic science on behalf of national security. Our generous benefits package includes:
§ PPO or High Deductible medical insurance with the same large nationwide network
§ Dental and vision insurance
§ Free basic life and disability insurance
§ Paid childbirth and parental leave
§ Award-winning 401(k) (6% matching plus 3.5% annually)
§ Learning opportunities and tuition assistance
§ Flexible schedules and time off (PTO and holidays)
§ Onsite gyms and wellness programs
§ Extensive relocation packages (outside a 50 mile radius)
Additional Details
Directive 206.2 - Employment with Triad requires a favorable decision by NNSA indicating employee is suitable under NNSA Supplemental Directive 206.2. Please note that this requirement applies only to citizens of the United States. Foreign nationals are subject to a similar requirement under DOE Order 142.3A.
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. Although New Mexico and other states have legalized the use of marijuana, use and possession of marijuana remain illegal under federal law. A positive drug test for marijuana will result in termination of employment, even if the use was pre-offer.
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 regard 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
How to Apply: How to Apply: Login to Your Account to Complete the Application Process
Click the Vacancy Name number (in blue) to view any job's details.
• Click Apply or Add to Basket to apply later. Tip: To apply for a job or save your basket, you must have a LANL jobs account. Instructions on How to Activate/Create a LANL Jobs Account:
Follow the instructions below if you have ever had an employee Z number, been a contractor, or received Los Alamos Lab insurance coverage to activate your account:
• Select the Click Here button if you have been employed with the Lab or received insurance coverage.
• Please enter only your first and last name and current email address (an email with your validation code will be sent to you) to activate the account currently in our system.
• Enter your validation code as described in the email you receive and complete the 3-page registration form. Your account is now active, and you can apply for jobs or save to your basket. Important: Enter the validation code within 15 days to activate your account or your account will be deactivated
Follow the instructions below if you if you have never been employed with the Lab or received insurance coverage to create an account:
• Select the Register button if you have never been employed with the Lab or received insurance coverage to Create an Account.
• From here, you will establish an account with username and password
How to Apply: How to Apply: Login to Your Account to Complete the Application Process
Click the Vacancy Name number (in blue) to view any job's details.
• Click Apply or Add to Basket to apply later. Tip: To apply for a job or save your basket, you must have a LANL jobs account.
If you experience any technical issues, please email applyhelp@lanl.gov for assistance.
